Eric P. Xing - RankMe

780 papers A* 175A 62B 10C 1Misc 4Journal 382Unranked 141

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	"Rebuilding" Statistics in the Age of AI: A Town Hall Discussion on Culture, Infrastructure, and Training. CoRR David L. Donoho, Jian Kang, Xihong Lin, Bhramar Mukherjee, Dan Nettleton, Rebecca Nugent, Abel Rodriguez, Eric P. Xing, Tian Zheng, Hongtu Zhu
2026	J	`jnl`	CellMaster: Collaborative Cell Type Annotation in Single-Cell Analysis. CoRR Zhen Wang, Yiming Gao, Jieyuan Liu, Enze Ma, Jefferson Chen, Mark Antkowiak, Mengzhou Hu, JungHo Kong, Dexter Pratt, Zhiting Hu, Wei Wang, Trey Ideker, Eric P. Xing
2026	J	`jnl`	FIRE-Bench: Evaluating Agents on the Rediscovery of Scientific Insights. CoRR Zhen Wang, Fan Bai, Zhongyan Luo, Jinyan Su, Kaiser Sun, Xinle Yu, Jieyuan Liu, Kun Zhou, Claire Cardie, Mark Dredze, Eric P. Xing, Zhiting Hu
2026	—	`conf`	In-context Learning of Evolving Data Streams with Tabular Foundational Models. KDD (1) Afonso Lourenço, João Gama, Eric P. Xing, Goreti Marreiros
2026	J	`jnl`	IsoCompute Playbook: Optimally Scaling Sampling Compute for LLM RL. CoRR Zhoujun Cheng, Yutao Xie, Yuxiao Qu, Amrith Setlur, Shibo Hao, Varad Pimpalkhute, Tongtong Liang, Feng Yao, Zhengzhong Liu, Eric P. Xing, Virginia Smith, Ruslan Salakhutdinov, Zhiting Hu, Taylor W. Killian, Aviral Kumar
2026	J	`jnl`	Mobile-O: Unified Multimodal Understanding and Generation on Mobile Device. CoRR Abdelrahman M. Shaker, Ahmed Heakl, Jaseel Muhammad Kaithakkodan, Ritesh Thawkar, Omkar Thawakar, Senmao Li, Hisham Cholakkal, Ian Reid, Eric P. Xing, Salman H. Khan, Fahad Shahbaz Khan
2026	J	`jnl`	Retrieval-Aware Distillation for Transformer-SSM Hybrids. CoRR Aviv Bick, Eric P. Xing, Albert Gu
2026	A*	`conf`	Vision-G1: Towards General Reasoning Vision-Language Models via Reinforcement Learning. AAAI Yuheng Zha, Kun Zhou, Yujia Wu, Yushu Wang, Jie Feng, Zhi Xu, Shibo Hao, Zhengzhong Liu, Eric P. Xing, Zhiting Hu
2026	J	`jnl`	World Reasoning Arena. CoRR Qiyue Gao, Kun Zhou, Jiannan Xiang, Zihan Liu, Dequan Yang, Junrong Chen, Arif Ahmad, Cong Zeng, Ganesh Bannur, Xinqi Huang, Zheqi Li, Yi Gu, Yichi Yang, Guangyi Liu, Zhiting Hu, Zhengzhong Liu, Eric P. Xing
2026	J	`jnl`	scPilot: Large Language Model Reasoning Toward Automated Single-Cell Analysis and Discovery. CoRR Yiming Gao, Zhen Wang, Jefferson Chen, Mark Antkowiak, Mengzhou Hu, JungHo Kong, Dexter Pratt, Jieyuan Liu, Enze Ma, Zhiting Hu, Eric P. Xing
2025	—	`conf`	Atlas-Chat: Adapting Large Language Models for Low-Resource Moroccan Arabic Dialect. COLING Workshops Guokan Shang, Hadi Abdine, Yousef Khoubrane, Amr Mohamed, Yassine Abbahaddou, Sofiane Ennadir, Imane Momayiz, Xuguang Ren, Eric Moulines, Preslav Nakov, Michalis Vazirgiannis, Eric P. Xing
2025	J	`jnl`	Beyond the Black Box: Identifiable Interpretation and Control in Generative Models via Causal Minimality. CoRR Lingjing Kong, Shaoan Xie, Guangyi Chen, Yuewen Sun, Xiangchen Song, Eric P. Xing, Kun Zhang
2025	J	`jnl`	Bridging Streaming Continual Learning via In-Context Large Tabular Models. CoRR Afonso Lourenço, João Gama, Eric P. Xing, Goreti Marreiros
2025	J	`jnl`	CITER: Collaborative Inference for Efficient Large Language Model Decoding with Token-Level Routing. CoRR Wenhao Zheng, Yixiao Chen, Weitong Zhang, Souvik Kundu, Yun Li, Zhengzhong Liu, Eric P. Xing, Hongyi Wang, Huaxiu Yao
2025	A*	`conf`	CReLeRI: Explainable, Concept-centric, Representation, Learning, Reasoning, and Interaction Video Analysis System. ACM Multimedia Michael Francis Perez, Yichi Yang, Yuheng Zha, Enze Ma, Danish Nisar Ahmed Tamboli, Haodi Ma, Reza Shahriari, Vyom Pathak, Dzmitry Kasinets, Rohith Venkatakrishnan, Daisy Zhe Wang, Jaime Ruiz, Eric D. Ragan, Zhiting Hu, Eric P. Xing, Jun-Yan Zhu
2025	A*	`conf`	Causal Representation Learning from Multimodal Biomedical Observations. ICLR Yuewen Sun, Lingjing Kong, Guangyi Chen, Loka Li, Gongxu Luo, Zijian Li, Yixuan Zhang, Yujia Zheng, Mengyue Yang, Petar Stojanov, Eran Segal, Eric P. Xing, Kun Zhang
2025	J	`jnl`	Critiques of World Models. CoRR Eric P. Xing, Mingkai Deng, Jinyu Hou, Zhiting Hu
2025	A*	`conf`	Data Mixing Optimization for Supervised Fine-Tuning of Large Language Models. ICML Yuan Li, Zhengzhong Liu, Eric P. Xing
2025	J	`jnl`	Data Mixing Optimization for Supervised Fine-Tuning of Large Language Models. CoRR Yuan Li, Zhengzhong Liu, Eric P. Xing
2025	J	`jnl`	Decentralized Arena: Towards Democratic and Scalable Automatic Evaluation of Language Models. CoRR Yanbin Yin, Kun Zhou, Zhen Wang, Zhaoxiang Zhang, Yifei Shao, Shibo Hao, Yi Gu, Jieyuan Liu, Somanshu Singla, Tianyang Liu, Eric P. Xing, Zhengzhong Liu, Haojian Jin, Zhiting Hu
2025	J	`jnl`	EvoLM: In Search of Lost Language Model Training Dynamics. CoRR Zhenting Qi, Fan Nie, Alexandre Alahi, James Zou, Himabindu Lakkaraju, Yilun Du, Eric P. Xing, Sham M. Kakade, Hanlin Zhang
2025	A*	`conf`	Follow My Instruction and Spill the Beans: Scalable Data Extraction from Retrieval-Augmented Generation Systems. ICLR Zhenting Qi, Hanlin Zhang, Eric P. Xing, Sham M. Kakade, Himabindu Lakkaraju
2025	J	`jnl`	How Does Controllability Emerge In Language Models During Pretraining? CoRR Jianshu She, Xinyue Li, Eric P. Xing, Zhengzhong Liu, Qirong Ho
2025	J	`jnl`	IMoRe: Implicit Program-Guided Reasoning for Human Motion Q&A. CoRR Chen Li, Chinthani Sugandhika, Ee Yeo Keat, Eric P. Xing, Hao Zhang, Hong Yang, Deepu Rajan, Basura Fernando
2025	J	`jnl`	In-context learning of evolving data streams with tabular foundational models. CoRR Afonso Lourenço, João Gama, Eric P. Xing, Goreti Marreiros
2025	J	`jnl`	K2-Think: A Parameter-Efficient Reasoning System. CoRR Zhoujun Cheng, Richard Fan, Shibo Hao, Taylor W. Killian, Haonan Li, Suqi Sun, Hector Ren, Alexander Moreno, Daqian Zhang, Tianjun Zhong, Yuxin Xiong, Yuanzhe Hu, Yutao Xie, Xudong Han, Yuqi Wang, Varad Pimpalkhute, Yonghao Zhuang, Aaryamonvikram Singh, Xuezhi Liang, Anze Xie, Jianshu She, Desai Fan, Chengqian Gao, Liqun Ma, Mikhail Yurochkin, John Maggs, Xuezhe Ma, Guowei He, Zhiting Hu, Zhengzhong Liu, Eric P. Xing
2025	J	`jnl`	LLM360 K2: Building a 65B 360-Open-Source Large Language Model from Scratch. CoRR Zhengzhong Liu, Bowen Tan, Hongyi Wang, Willie Neiswanger, Tianhua Tao, Haonan Li, Fajri Koto, Yuqi Wang, Suqi Sun, Omkar Pangarkar, Richard Fan, Yi Gu, Victor Miller, Liqun Ma, Liping Tang, Nikhil Ranjan, Yonghao Zhuang, Guowei He, Renxi Wang, Mingkai Deng, Robin Algayres, Yuanzhi Li, Zhiqiang Shen, Preslav Nakov, Eric P. Xing
2025	A*	`conf`	Learning Vision and Language Concepts for Controllable Image Generation. ICML Shaoan Xie, Lingjing Kong, Yujia Zheng, Zeyu Tang, Eric P. Xing, Guangyi Chen, Kun Zhang
2025	—	`conf`	Linear Steerability in Language Models: When It Emerges and How It Evolves. EMNLP (Findings) Jianshu She, Xinyue Li, Eric P. Xing, Zhengzhong Liu, Qirong Ho
2025	J	`jnl`	Log-Linear Attention. CoRR Han Guo, Songlin Yang, Tarushii Goel, Eric P. Xing, Tri Dao, Yoon Kim
2025	J	`jnl`	MegaMath: Pushing the Limits of Open Math Corpora. CoRR Fan Zhou, Zengzhi Wang, Nikhil Ranjan, Zhoujun Cheng, Liping Tang, Guowei He, Zhengzhong Liu, Eric P. Xing
2025	J	`jnl`	MuCHEx: A Multimodal Conversational Debugging Tool for Interactive Visual Exploration of Hierarchical Object Classification. IEEE Computer Graphics and Applications Reza Shahriari, Yichi Yang, Danish Nisar Ahmed Tamboli, Michael Francis Perez, Yuheng Zha, Jinyu Hou, Mingkai Deng, Eric D. Ragan, Jaime Ruiz, Daisy Zhe Wang, Zhiting Hu, Eric P. Xing
2025	J	`jnl`	Nile-Chat: Egyptian Language Models for Arabic and Latin Scripts. CoRR Guokan Shang, Hadi Abdine, Ahmad Chamma, Amr Mohamed, Mohamed Anwar, Abdelaziz Bounhar, Omar El Harrouss, Preslav Nakov, Michalis Vazirgiannis, Eric P. Xing
2025	J	`jnl`	PAN: A World Model for General, Interactable, and Long-Horizon World Simulation. CoRR Jiannan Xiang, Yi Gu, Zihan Liu, Zeyu Feng, Qiyue Gao, Yiyan Hu, Benhao Huang, Guangyi Liu, Yichi Yang, Kun Zhou, Davit Abrahamyan, Arif Ahmad, Ganesh Bannur, Junrong Chen, Kimi Chen, Mingkai Deng, Ruobing Han, Xinqi Huang, Haoqiang Kang, Zheqi Li, Enze Ma, Hector Ren, Yashowardhan Shinde, Rohan Shingre, Ramsundar Tanikella, Kaiming Tao, Dequan Yang, Xinle Yu, Cong Zeng, Binglin Zhou, Hector Liu, Zhiting Hu, Eric P. Xing
2025	J	`jnl`	PRISM: Enhancing Protein Inverse Folding through Fine-Grained Retrieval on Structure-Sequence Multimodal Representations. CoRR Sazan Mahbub, Souvik Kundu, Eric P. Xing
2025	J	`jnl`	Pruning Spurious Subgraphs for Graph Out-of-Distribtuion Generalization. CoRR Tianjun Yao, Haoxuan Li, Yongqiang Chen, Tongliang Liu, Le Song, Eric P. Xing, Zhiqiang Shen
2025	J	`jnl`	Response to Promises and Pitfalls of Deep Kernel Learning. CoRR Andrew Gordon Wilson, Zhiting Hu, Ruslan Salakhutdinov, Eric P. Xing
2025	J	`jnl`	Revisiting Reinforcement Learning for LLM Reasoning from A Cross-Domain Perspective. CoRR Zhoujun Cheng, Shibo Hao, Tianyang Liu, Fan Zhou, Yutao Xie, Feng Yao, Yuexin Bian, Yonghao Zhuang, Nilabjo Dey, Yuheng Zha, Yi Gu, Kun Zhou, Yuqi Wang, Yuan Li, Richard Fan, Jianshu She, Chengqian Gao, Abulhair Saparov, Haonan Li, Taylor W. Killian, Mikhail Yurochkin, Zhengzhong Liu, Eric P. Xing, Zhiting Hu
2025	A*	`conf`	Scaling Long Context Training Data by Long-Distance Referrals. ICLR Yonghao Zhuang, Lanxiang Hu, Longfei Yun, Souvik Kundu, Zhengzhong Liu, Eric P. Xing, Hao Zhang
2025	J	`jnl`	SimuRA: Towards General Goal-Oriented Agent via Simulative Reasoning Architecture with LLM-Based World Model. CoRR Mingkai Deng, Jinyu Hou, Yilin Shen, Hongxia Jin, Graham Neubig, Zhiting Hu, Eric P. Xing
2025	A*	`conf`	SmartCLIP: Modular Vision-language Alignment with Identification Guarantees. CVPR Shaoan Xie, Lingjing, Yujia Zheng, Yu Yao, Zeyu Tang, Eric P. Xing, Guangyi Chen, Kun Zhang
2025	J	`jnl`	SmartCLIP: Modular Vision-language Alignment with Identification Guarantees. CoRR Shaoan Xie, Lingjing Kong, Yujia Zheng, Yu Yao, Zeyu Tang, Eric P. Xing, Guangyi Chen, Kun Zhang
2025	J	`jnl`	Step-Aware Policy Optimization for Reasoning in Diffusion Large Language Models. CoRR Shaoan Xie, Lingjing Kong, Xiangchen Song, Xinshuai Dong, Guangyi Chen, Eric P. Xing, Kun Zhang
2025	A*	`conf`	Synthesizing Privacy-Preserving Text Data via Finetuning without Finetuning Billion-Scale LLMs. ICML Bowen Tan, Zheng Xu, Eric P. Xing, Zhiting Hu, Shanshan Wu
2025	J	`jnl`	Synthesizing Privacy-Preserving Text Data via Finetuning without Finetuning Billion-Scale LLMs. CoRR Bowen Tan, Zheng Xu, Eric P. Xing, Zhiting Hu, Shanshan Wu
2025	—	`conf`	Token Level Routing Inference System for Edge Devices. ACL (3) Jianshu She, Wenhao Zheng, Zhengzhong Liu, Hongyi Wang, Eric P. Xing, Huaxiu Yao, Qirong Ho
2025	J	`jnl`	Token Level Routing Inference System for Edge Devices. CoRR Jianshu She, Wenhao Zheng, Zhengzhong Liu, Hongyi Wang, Eric P. Xing, Huaxiu Yao, Qirong Ho
2025	J	`jnl`	Towards Understanding Extrapolation: a Causal Lens. CoRR Lingjing Kong, Guangyi Chen, Petar Stojanov, Haoxuan Li, Eric P. Xing, Kun Zhang
2025	A*	`conf`	Understanding the Skill Gap in Recurrent Language Models: The Role of the Gather-and-Aggregate Mechanism. ICML Aviv Bick, Eric P. Xing, Albert Gu
2025	J	`jnl`	Understanding the Skill Gap in Recurrent Language Models: The Role of the Gather-and-Aggregate Mechanism. CoRR Aviv Bick, Eric P. Xing, Albert Gu
2025	A*	`conf`	VideoGLaMM : A Large Multimodal Model for Pixel-Level Visual Grounding in Videos. CVPR Shehan Munasinghe, Hanan Gani, Wenqi Zhu, Jiale Cao, Eric P. Xing, Fahad Shahbaz Khan, Salman H. Khan
2025	J	`jnl`	Vision-G1: Towards General Vision Language Reasoning with Multi-Domain Data Curation. CoRR Yuheng Zha, Kun Zhou, Yujia Wu, Yushu Wang, Jie Feng, Zhi Xu, Shibo Hao, Zhengzhong Liu, Eric P. Xing, Zhiting Hu
2025	J	`jnl`	lmgame-Bench: How Good are LLMs at Playing Games? CoRR Lanxiang Hu, Mingjia Huo, Yuxuan Zhang, Haoyang Yu, Eric P. Xing, Ion Stoica, Tajana Rosing, Haojian Jin, Hao Zhang
2024	—	`conf`	A Study on the Calibration of In-context Learning. NAACL-HLT Hanlin Zhang, Yifan Zhang, Yaodong Yu, Dhruv Madeka, Dean P. Foster, Eric P. Xing, Himabindu Lakkaraju, Sham M. Kakade
2024	J	`jnl`	An exploratory study of self-supervised pre-training on partially supervised multi-label classification on chest X-ray images. Appl. Soft Comput. Nanqing Dong, Michael Kampffmeyer, Haoyang Su, Eric P. Xing
2024	J	`jnl`	Atlas-Chat: Adapting Large Language Models for Low-Resource Moroccan Arabic Dialect. CoRR Guokan Shang, Hadi Abdine, Yousef Khoubrane, Amr Mohamed, Yassine Abbahaddou, Sofiane Ennadir, Imane Momayiz, Xuguang Ren, Eric Moulines, Preslav Nakov, Michalis Vazirgiannis, Eric P. Xing
2024	J	`jnl`	AttentionPert: accurately modeling multiplexed genetic perturbations with multi-scale effects. Bioinform. Ding Bai, Caleb N. Ellington, Shentong Mo, Le Song, Eric P. Xing
2024	J	`jnl`	Causal Representation Learning from Multimodal Biological Observations. CoRR Yuewen Sun, Lingjing Kong, Guangyi Chen, Loka Li, Gongxu Luo, Zijian Li, Yixuan Zhang, Yujia Zheng, Mengyue Yang, Petar Stojanov, Eran Segal, Eric P. Xing, Kun Zhang
2024	J	`jnl`	Confidence Matters: Revisiting Intrinsic Self-Correction Capabilities of Large Language Models. CoRR Loka Li, Guangyi Chen, Yusheng Su, Zhenhao Chen, Yixuan Zhang, Eric P. Xing, Kun Zhang
2024	A*	`conf`	Contextualized Policy Recovery: Modeling and Interpreting Medical Decisions with Adaptive Imitation Learning. ICML Jannik Deuschel, Caleb Ellington, Yingtao Luo, Benjamin J. Lengerich, Pascal Friederich, Eric P. Xing
2024	J	`jnl`	Contextualized: Heterogeneous Modeling Toolbox. J. Open Source Softw. Caleb N. Ellington, Benjamin J. Lengerich, Wesley Lo, Aaron Alvarez, Andrea Rubbi, Manolis Kellis, Eric P. Xing
2024	J	`jnl`	Counterfactual Generation with Identifiability Guarantees. CoRR Hanqi Yan, Lingjing Kong, Lin Gui, Yuejie Chi, Eric P. Xing, Yulan He, Kun Zhang
2024	J	`jnl`	Crystal: Illuminating LLM Abilities on Language and Code. CoRR Tianhua Tao, Junbo Li, Bowen Tan, Hongyi Wang, William Marshall, Bhargav Kanakiya, Joel Hestness, Natalia Vassilieva, Zhiqiang Shen, Eric P. Xing, Zhengzhong Liu
2024	J	`jnl`	Defending Against Poisoning Attacks in Federated Learning With Blockchain. IEEE Trans. Artif. Intell. Nanqing Dong, Zhipeng Wang, Jiahao Sun, Michael Kampffmeyer, William J. Knottenbelt, Eric P. Xing
2024	—	`conf`	Does Compressing Activations Help Model Parallel Training? MLSys Song Bian, Dacheng Li, Hongyi Wang, Eric P. Xing, Shivaram Venkataraman
2024	A*	`conf`	Dynamic Rewarding with Prompt Optimization Enables Tuning-free Self-Alignment of Language Models. EMNLP Somanshu Singla, Zhen Wang, Tianyang Liu, Abdullah Ashfaq, Zhiting Hu, Eric P. Xing
2024	J	`jnl`	Dynamic Rewarding with Prompt Optimization Enables Tuning-free Self-Alignment of Language Models. CoRR Somanshu Singla, Zhen Wang, Tianyang Liu, Abdullah Ashfaq, Zhiting Hu, Eric P. Xing
2024	A*	`conf`	Efficient Test-Time Adaptation of Vision-Language Models. CVPR Adilbek Karmanov, Dayan Guan, Shijian Lu, Abdulmotaleb El Saddik, Eric P. Xing
2024	J	`jnl`	Efficient Test-Time Adaptation of Vision-Language Models. CoRR Adilbek Karmanov, Dayan Guan, Shijian Lu, Abdulmotaleb El Saddik, Eric P. Xing
2024	—	`conf`	Evaluating Step-by-Step Reasoning through Symbolic Verification. NAACL-HLT (Findings) Yifan Zhang, Hanlin Zhang, Li Li, Eric P. Xing
2024	—	`conf`	Fast Matrix Multiplications for Lookup Table-Quantized LLMs. EMNLP (Findings) Han Guo, William Brandon, Radostin Cholakov, Jonathan Ragan-Kelley, Eric P. Xing, Yoon Kim
2024	J	`jnl`	Fast Matrix Multiplications for Lookup Table-Quantized LLMs. CoRR Han Guo, William Brandon, Radostin Cholakov, Jonathan Ragan-Kelley, Eric P. Xing, Yoon Kim
2024	J	`jnl`	Follow My Instruction and Spill the Beans: Scalable Data Extraction from Retrieval-Augmented Generation Systems. CoRR Zhenting Qi, Hanlin Zhang, Eric P. Xing, Sham M. Kakade, Himabindu Lakkaraju
2024	A*	`conf`	FreGS: 3D Gaussian Splatting with Progressive Frequency Regularization. CVPR Jiahui Zhang, Fangneng Zhan, Muyu Xu, Shijian Lu, Eric P. Xing
2024	J	`jnl`	FreGS: 3D Gaussian Splatting with Progressive Frequency Regularization. CoRR Jiahui Zhang, Fangneng Zhan, Muyu Xu, Shijian Lu, Eric P. Xing
2024	A*	`conf`	Fusing Models with Complementary Expertise. ICLR Hongyi Wang, Felipe Maia Polo, Yuekai Sun, Souvik Kundu, Eric P. Xing, Mikhail Yurochkin
2024	A*	`conf`	GLaMM: Pixel Grounding Large Multimodal Model. CVPR Hanoona Abdul Rasheed, Muhammad Maaz, Sahal Shaji Mullappilly, Abdelrahman M. Shaker, Salman H. Khan, Hisham Cholakkal, Rao Muhammad Anwer, Eric P. Xing, Ming-Hsuan Yang, Fahad Shahbaz Khan
2024	J	`jnl`	Generating, Reconstructing, and Representing Discrete and Continuous Data: Generalized Diffusion with Learnable Encoding-Decoding. CoRR Guangyi Liu, Yu Wang, Zeyu Feng, Qiyu Wu, Liping Tang, Yuan Gao, Zhen Li, Shuguang Cui, Julian J. McAuley, Eric P. Xing, Zichao Yang, Zhiting Hu
2024	J	`jnl`	Iterative Graph Self-Distillation. IEEE Trans. Knowl. Data Eng. Hanlin Zhang, Shuai Lin, Weiyang Liu, Pan Zhou, Jian Tang, Xiaodan Liang, Eric P. Xing
2024	A*	`conf`	LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset. ICLR Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Tianle Li, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zhuohan Li, Zi Lin, Eric P. Xing, Joseph E. Gonzalez, Ion Stoica, Hao Zhang
2024	A*	`conf`	LQ-LoRA: Low-rank plus Quantized Matrix Decomposition for Efficient Language Model Finetuning. ICLR Han Guo, Philip Greengard, Eric P. Xing, Yoon Kim
2024	A*	`conf`	Learning Discrete Concepts in Latent Hierarchical Models. NeurIPS Lingjing Kong, Guangyi Chen, Biwei Huang, Eric P. Xing, Yuejie Chi, Kun Zhang
2024	J	`jnl`	Learning Discrete Concepts in Latent Hierarchical Models. CoRR Lingjing Kong, Guangyi Chen, Biwei Huang, Eric P. Xing, Yuejie Chi, Kun Zhang
2024	J	`jnl`	Learning to Prompt Segment Anything Models. CoRR Jiaxing Huang, Kai Jiang, Jingyi Zhang, Han Qiu, Lewei Lu, Shijian Lu, Eric P. Xing
2024	A	`conf`	MixMask: Revisiting Masking Strategy for Siamese ConvNets. BMVC Kirill Vishniakov, Eric P. Xing, Zhiqiang Shen
2024	J	`jnl`	MobiLlama: Towards Accurate and Lightweight Fully Transparent GPT. CoRR Omkar Thawakar, Ashmal Vayani, Salman H. Khan, Hisham Cholakkal, Rao Muhammad Anwer, Michael Felsberg, Tim Baldwin, Eric P. Xing, Fahad Shahbaz Khan
2024	J	`jnl`	Pandora: Towards General World Model with Natural Language Actions and Video States. CoRR Jiannan Xiang, Guangyi Liu, Yi Gu, Qiyue Gao, Yuting Ning, Yuheng Zha, Zeyu Feng, Tianhua Tao, Shibo Hao, Yemin Shi, Zhengzhong Liu, Eric P. Xing, Zhiting Hu
2024	J	`jnl`	Patient-Specific Models of Treatment Effects Explain Heterogeneity in Tuberculosis. CoRR Ethan Wu, Caleb Ellington, Benjamin J. Lengerich, Eric P. Xing
2024	A*	`conf`	Position: TrustLLM: Trustworthiness in Large Language Models. ICML Yue Huang, Lichao Sun, Haoran Wang, Siyuan Wu, Qihui Zhang, Yuan Li, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Hanchi Sun, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bertie Vidgen, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, Joaquin Vanschoren, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao
2024	A*	`conf`	PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization. ICLR Xinyuan Wang, Chenxi Li, Zhen Wang, Fan Bai, Haotian Luo, Jiayou Zhang, Nebojsa Jojic, Eric P. Xing, Zhiting Hu
2024	J	`jnl`	Prototypical Graph Contrastive Learning. IEEE Trans. Neural Networks Learn. Syst. Shuai Lin, Chen Liu, Pan Zhou, Zi-Yuan Hu, Shuojia Wang, Ruihui Zhao, Yefeng Zheng, Liang Lin, Eric P. Xing, Xiaodan Liang
2024	—	`conf`	RedCoast: A Lightweight Tool to Automate Distributed Training of LLMs on Any GPU/TPUs. NAACL (Demonstrations) Bowen Tan, Yun Zhu, Lijuan Liu, Hongyi Wang, Yonghao Zhuang, Jindong Chen, Eric P. Xing, Zhiting Hu
2024	J	`jnl`	Reducing Hyperparameter Tuning Costs in ML, Vision and Language Model Training Pipelines via Memoization-Awareness. CoRR Abdelmajid Essofi, Ridwan Salahuddeen, Munachiso Nwadike, Elnura Zhalieva, Kun Zhang, Eric P. Xing, Willie Neiswanger, Qirong Ho
2024	J	`jnl`	SPRINT Enables Interpretable and Ultra-Fast Virtual Screening against Thousands of Proteomes. CoRR Andrew T. McNutt, Abhinav Adduri, Caleb N. Ellington, Monica T. Dayao, Eric P. Xing, Hosein Mohimani, David Ryan Koes
2024	J	`jnl`	Semantic-Aligned Matching for Enhanced DETR Convergence and Multi-Scale Feature Fusion. Int. J. Comput. Vis. Gongjie Zhang, Zhipeng Luo, Jiaxing Huang, Shijian Lu, Eric P. Xing
2024	J	`jnl`	Toward AI-Driven Digital Organism: Multiscale Foundation Models for Predicting, Simulating and Programming Biology at All Levels. CoRR Le Song, Eran Segal, Eric P. Xing
2024	J	`jnl`	Toward Inference-optimal Mixture-of-Expert Large Language Models. CoRR Longfei Yun, Yonghao Zhuang, Yao Fu, Eric P. Xing, Hao Zhang
2024	A*	`conf`	Towards Understanding Extrapolation: a Causal Lens. NeurIPS Lingjing Kong, Guangyi Chen, Petar Stojanov, Haoxuan Li, Eric P. Xing, Kun Zhang
2024	A*	`conf`	Transformers to SSMs: Distilling Quadratic Knowledge to Subquadratic Models. NeurIPS Aviv Bick, Kevin Y. Li, Eric P. Xing, J. Zico Kolter, Albert Gu
2024	J	`jnl`	Transformers to SSMs: Distilling Quadratic Knowledge to Subquadratic Models. CoRR Aviv Bick, Kevin Y. Li, Eric P. Xing, J. Zico Kolter, Albert Gu
2024	J	`jnl`	TrustLLM: Trustworthiness in Large Language Models. CoRR Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yue Zhao
2024	A*	`conf`	Unified Generation, Reconstruction, and Representation: Generalized Diffusion with Adaptive Latent Encoding-Decoding. ICML Guangyi Liu, Yu Wang, Zeyu Feng, Qiyu Wu, Liping Tang, Yuan Gao, Zhen Li, Shuguang Cui, Julian J. McAuley, Zichao Yang, Eric P. Xing, Zhiting Hu
2024	J	`jnl`	VideoGLaMM: A Large Multimodal Model for Pixel-Level Visual Grounding in Videos. CoRR Shehan Munasinghe, Hanan Gani, Wenqi Zhu, Jiale Cao, Eric P. Xing, Fahad Shahbaz Khan, Salman Khan
2024	A*	`conf`	Web2Code: A Large-scale Webpage-to-Code Dataset and Evaluation Framework for Multimodal LLMs. NeurIPS Sukmin Yun, Haokun Lin, Rusiru Thushara, Mohammad Qazim Bhat, Yongxin Wang, Zutao Jiang, Mingkai Deng, Jinhong Wang, Tianhua Tao, Junbo Li, Haonan Li, Preslav Nakov, Timothy Baldwin, Zhengzhong Liu, Eric P. Xing, Xiaodan Liang, Zhiqiang Shen
2024	J	`jnl`	Web2Code: A Large-scale Webpage-to-Code Dataset and Evaluation Framework for Multimodal LLMs. CoRR Sukmin Yun, Haokun Lin, Rusiru Thushara, Mohammad Qazim Bhat, Yongxin Wang, Zutao Jiang, Mingkai Deng, Jinhong Wang, Tianhua Tao, Junbo Li, Haonan Li, Preslav Nakov, Timothy Baldwin, Zhengzhong Liu, Eric P. Xing, Xiaodan Liang, Zhiqiang Shen
2024	J	`jnl`	What is Your Data Worth to GPT? LLM-Scale Data Valuation with Influence Functions. CoRR Sang Keun Choe, Hwijeen Ahn, Juhan Bae, Kewen Zhao, Minsoo Kang, Youngseog Chung, Adithya Pratapa, Willie Neiswanger, Emma Strubell, Teruko Mitamura, Jeff G. Schneider, Eduard H. Hovy, Roger B. Grosse, Eric P. Xing
2023	J	`jnl`	3D Open-vocabulary Segmentation with Foundation Models. CoRR Kunhao Liu, Fangneng Zhan, Jiahui Zhang, Muyu Xu, Yingchen Yu, Abdulmotaleb El Saddik, Christian Theobalt, Eric P. Xing, Shijian Lu
2023	A*	`conf`	3D Semantic Segmentation in the Wild: Learning Generalized Models for Adverse-Condition Point Clouds. CVPR Aoran Xiao, Jiaxing Huang, Weihao Xuan, Ruijie Ren, Kangcheng Liu, Dayan Guan, Abdulmotaleb El Saddik, Shijian Lu, Eric P. Xing
2023	J	`jnl`	3D Semantic Segmentation in the Wild: Learning Generalized Models for Adverse-Condition Point Clouds. CoRR Aoran Xiao, Jiaxing Huang, Weihao Xuan, Ruijie Ren, Kangcheng Liu, Dayan Guan, Abdulmotaleb El Saddik, Shijian Lu, Eric P. Xing
2023	J	`jnl`	A Study on the Calibration of In-context Learning. CoRR Hanlin Zhang, Yifan Zhang, Yaodong Yu, Dhruv Madeka, Dean P. Foster, Eric P. Xing, Himabindu Lakkaraju, Sham M. Kakade
2023	—	`conf`	BertNet: Harvesting Knowledge Graphs with Arbitrary Relations from Pretrained Language Models. ACL (Findings) Shibo Hao, Bowen Tan, Kaiwen Tang, Bin Ni, Xiyan Shao, Hengzhe Zhang, Eric P. Xing, Zhiting Hu
2023	A*	`conf`	Betty: An Automatic Differentiation Library for Multilevel Optimization. ICLR Sang Keun Choe, Willie Neiswanger, Pengtao Xie, Eric P. Xing
2023	A*	`conf`	Cappy: Outperforming and Boosting Large Multi-Task LMs with a Small Scorer. NeurIPS Bowen Tan, Yun Zhu, Lijuan Liu, Eric P. Xing, Zhiting Hu, Jindong Chen
2023	J	`jnl`	Cappy: Outperforming and Boosting Large Multi-Task LMs with a Small Scorer. CoRR Bowen Tan, Yun Zhu, Lijuan Liu, Eric P. Xing, Zhiting Hu, Jindong Chen
2023	J	`jnl`	Contextualized Machine Learning. CoRR Benjamin J. Lengerich, Caleb N. Ellington, Andrea Rubbi, Manolis Kellis, Eric P. Xing
2023	J	`jnl`	Contextualized Policy Recovery: Modeling and Interpreting Medical Decisions with Adaptive Imitation Learning. CoRR Jannik Deuschel, Caleb N. Ellington, Benjamin J. Lengerich, Yingtao Luo, Pascal Friederich, Eric P. Xing
2023	A*	`conf`	Counterfactual Generation with Identifiability Guarantees. NeurIPS Hanqi Yan, Lingjing Kong, Lin Gui, Yuejie Chi, Eric P. Xing, Yulan He, Kun Zhang
2023	—	`conf`	Cuttlefish: Low-Rank Model Training without All the Tuning. MLSys Hongyi Wang, Saurabh Agarwal, Pongsakorn U.-Chupala, Yoshiki Tanaka, Eric P. Xing, Dimitris Papailiopoulos
2023	J	`jnl`	Cuttlefish: Low-Rank Model Training without All the Tuning. CoRR Hongyi Wang, Saurabh Agarwal, Pongsakorn U.-Chupala, Yoshiki Tanaka, Eric P. Xing, Dimitris S. Papailiopoulos
2023	J	`jnl`	Defending Against Malicious Behaviors in Federated Learning with Blockchain. CoRR Nanqing Dong, Zhipeng Wang, Jiahao Sun, Michael Kampffmeyer, Yizhe Wen, Shuoying Zhang, William J. Knottenbelt, Eric P. Xing
2023	J	`jnl`	Does compressing activations help model parallel training? CoRR Song Bian, Dacheng Li, Hongyi Wang, Eric P. Xing, Shivaram Venkataraman
2023	J	`jnl`	Exploring Transformer Backbones for Heterogeneous Treatment Effect Estimation. Trans. Mach. Learn. Res. Yifan Zhang, Hanlin Zhang, Zachary Chase Lipton, Li Erran Li, Eric P. Xing
2023	A*	`conf`	FedNAR: Federated Optimization with Normalized Annealing Regularization. NeurIPS Junbo Li, Ang Li, Chong Tian, Qirong Ho, Eric P. Xing, Hongyi Wang
2023	J	`jnl`	FedNAR: Federated Optimization with Normalized Annealing Regularization. CoRR Junbo Li, Ang Li, Chong Tian, Qirong Ho, Eric P. Xing, Hongyi Wang
2023	A*	`conf`	Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach. ICLR Han Guo, Philip Greengard, Hongyi Wang, Andrew Gelman, Yoon Kim, Eric P. Xing
2023	J	`jnl`	Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach. CoRR Han Guo, Philip Greengard, Hongyi Wang, Andrew Gelman, Yoon Kim, Eric P. Xing
2023	J	`jnl`	Federated Partially Supervised Learning With Limited Decentralized Medical Images. IEEE Trans. Medical Imaging Nanqing Dong, Michael Kampffmeyer, Irina Voiculescu, Eric P. Xing
2023	J	`jnl`	Fusing Models with Complementary Expertise. CoRR Hongyi Wang, Felipe Maia Polo, Yuekai Sun, Souvik Kundu, Eric P. Xing, Mikhail Yurochkin
2023	J	`jnl`	GLaMM: Pixel Grounding Large Multimodal Model. CoRR Hanoona Abdul Rasheed, Muhammad Maaz, Sahal Shaji Mullappilly, Abdelrahman M. Shaker, Salman H. Khan, Hisham Cholakkal, Rao Muhammad Anwer, Eric P. Xing, Ming-Hsuan Yang, Fahad Shahbaz Khan
2023	A*	`conf`	Identification of Nonlinear Latent Hierarchical Models. NeurIPS Lingjing Kong, Biwei Huang, Feng Xie, Eric P. Xing, Yuejie Chi, Kun Zhang
2023	J	`jnl`	Identification of Nonlinear Latent Hierarchical Models. CoRR Lingjing Kong, Biwei Huang, Feng Xie, Eric P. Xing, Yuejie Chi, Kun Zhang
2023	—	`conf`	Improved Logical Reasoning of Language Models via Differentiable Symbolic Programming. ACL (Findings) Hanlin Zhang, Jiani Huang, Ziyang Li, Mayur Naik, Eric P. Xing
2023	J	`jnl`	Improved Logical Reasoning of Language Models via Differentiable Symbolic Programming. CoRR Hanlin Zhang, Jiani Huang, Ziyang Li, Mayur Naik, Eric P. Xing
2023	J	`jnl`	Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language Models. CoRR Neha Sengupta, Sunil Kumar Sahu, Bokang Jia, Satheesh Katipomu, Haonan Li, Fajri Koto, Osama Mohammed Afzal, Samta Kamboj, Onkar Pandit, Rahul Pal, Lalit Pradhan, Zain Muhammad Mujahid, Massa Baali, Alham Fikri Aji, Zhengzhong Liu, Andy Hock, Andrew Feldman, Jonathan Lee, Andrew Jackson, Preslav Nakov, Timothy Baldwin, Eric P. Xing
2023	A*	`conf`	Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena. NeurIPS Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric P. Xing, Hao Zhang, Joseph E. Gonzalez, Ion Stoica
2023	J	`jnl`	Judging LLM-as-a-judge with MT-Bench and Chatbot Arena. CoRR Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric P. Xing, Hao Zhang, Joseph E. Gonzalez, Ion Stoica
2023	A*	`conf`	KD-DLGAN: Data Limited Image Generation via Knowledge Distillation. CVPR Kaiwen Cui, Yingchen Yu, Fangneng Zhan, Shengcai Liao, Shijian Lu, Eric P. Xing
2023	J	`jnl`	KD-DLGAN: Data Limited Image Generation via Knowledge Distillation. CoRR Kaiwen Cui, Yingchen Yu, Fangneng Zhan, Shengcai Liao, Shijian Lu, Eric P. Xing
2023	J	`jnl`	LLM360: Towards Fully Transparent Open-Source LLMs. CoRR Zhengzhong Liu, Aurick Qiao, Willie Neiswanger, Hongyi Wang, Bowen Tan, Tianhua Tao, Junbo Li, Yuqi Wang, Suqi Sun, Omkar Pangarkar, Richard Fan, Yi Gu, Victor Miller, Yonghao Zhuang, Guowei He, Haonan Li, Fajri Koto, Liping Tang, Nikhil Ranjan, Zhiqiang Shen, Xuguang Ren, Roberto Iriondo, Cun Mu, Zhiting Hu, Mark Schulze, Preslav Nakov, Tim Baldwin, Eric P. Xing
2023	J	`jnl`	LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset. CoRR Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Tianle Li, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zhuohan Li, Zi Lin, Eric P. Xing, Joseph E. Gonzalez, Ion Stoica, Hao Zhang
2023	J	`jnl`	LQ-LoRA: Low-rank Plus Quantized Matrix Decomposition for Efficient Language Model Finetuning. CoRR Han Guo, Philip Greengard, Eric P. Xing, Yoon Kim
2023	J	`jnl`	LightSeq: Sequence Level Parallelism for Distributed Training of Long Context Transformers. CoRR Dacheng Li, Rulin Shao, Anze Xie, Eric P. Xing, Joseph E. Gonzalez, Ion Stoica, Xuezhe Ma, Hao Zhang
2023	A*	`conf`	MPCFORMER: Fast, Performant and Provate Transformer Inference with MPC. ICLR Dacheng Li, Hongyi Wang, Rulin Shao, Han Guo, Eric P. Xing, Hao Zhang
2023	A*	`conf`	Making Scalable Meta Learning Practical. NeurIPS Sang Keun Choe, Sanket Vaibhav Mehta, Hwijeen Ahn, Willie Neiswanger, Pengtao Xie, Emma Strubell, Eric P. Xing
2023	J	`jnl`	Making Scalable Meta Learning Practical. CoRR Sang Keun Choe, Sanket Vaibhav Mehta, Hwijeen Ahn, Willie Neiswanger, Pengtao Xie, Emma Strubell, Eric P. Xing
2023	J	`jnl`	Memory-adaptive Depth-wise Heterogenous Federated Learning. CoRR Kai Zhang, Yutong Dai, Hongyi Wang, Eric P. Xing, Xun Chen, Lichao Sun
2023	J	`jnl`	Meta-DETR: Image-Level Few-Shot Detection With Inter-Class Correlation Exploitation. IEEE Trans. Pattern Anal. Mach. Intell. Gongjie Zhang, Zhipeng Luo, Kaiwen Cui, Shijian Lu, Eric P. Xing
2023	J	`jnl`	Multimodal Image Synthesis and Editing: The Generative AI Era. IEEE Trans. Pattern Anal. Mach. Intell. Fangneng Zhan, Yingchen Yu, Rongliang Wu, Jiahui Zhang, Shijian Lu, Lingjie Liu, Adam Kortylewski, Christian Theobalt, Eric P. Xing
2023	—	`ch.`	Neural-Symbolic Interaction and Co-Evolving. Compendium of Neurosymbolic Artificial Intelligence Bowen Tan, Shibo Hao, Eric P. Xing, Zhiting Hu
2023	—	`conf`	On Optimizing the Communication of Model Parallelism. MLSys Yonghao Zhuang, Lianmin Zheng, Zhuohan Li, Eric P. Xing, Qirong Ho, Joseph Gonzalez, Ion Stoica, Hao Zhang, Hexu Zhao
2023	J	`jnl`	One-for-All: Generalized LoRA for Parameter-Efficient Fine-tuning. CoRR Arnav Chavan, Zhuang Liu, Deepak K. Gupta, Eric P. Xing, Zhiqiang Shen
2023	J	`jnl`	PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization. CoRR Xinyuan Wang, Chenxi Li, Zhen Wang, Fan Bai, Haotian Luo, Jiayou Zhang, Nebojsa Jojic, Eric P. Xing, Zhiting Hu
2023	J	`jnl`	Redco: A Lightweight Tool to Automate Distributed Training of LLMs on Any GPU/TPUs. CoRR Bowen Tan, Yun Zhu, Lijuan Liu, Hongyi Wang, Yonghao Zhuang, Jindong Chen, Eric P. Xing, Zhiting Hu
2023	J	`jnl`	SegMix: A Simple Structure-Aware Data Augmentation Method. CoRR Yuxin Pei, Pushkar Bhuse, Zhengzhong Liu, Eric P. Xing
2023	J	`jnl`	SlimPajama-DC: Understanding Data Combinations for LLM Training. CoRR Zhiqiang Shen, Tianhua Tao, Liqun Ma, Willie Neiswanger, Zhengzhong Liu, Hongyi Wang, Bowen Tan, Joel Hestness, Natalia Vassilieva, Daria Soboleva, Eric P. Xing
2023	A*	`conf`	Squeeze, Recover and Relabel: Dataset Condensation at ImageNet Scale From A New Perspective. NeurIPS Zeyuan Yin, Eric P. Xing, Zhiqiang Shen
2023	J	`jnl`	Squeeze, Recover and Relabel: Dataset Condensation at ImageNet Scale From A New Perspective. CoRR Zeyuan Yin, Eric P. Xing, Zhiqiang Shen
2023	A*	`conf`	StyleRF: Zero-Shot 3D Style Transfer of Neural Radiance Fields. CVPR Kunhao Liu, Fangneng Zhan, Yiwen Chen, Jiahui Zhang, Yingchen Yu, Abdulmotaleb El Saddik, Shijian Lu, Eric P. Xing
2023	J	`jnl`	StyleRF: Zero-shot 3D Style Transfer of Neural Radiance Fields. CoRR Kunhao Liu, Fangneng Zhan, Yiwen Chen, Jiahui Zhang, Yingchen Yu, Abdulmotaleb El Saddik, Shijian Lu, Eric P. Xing
2023	A*	`conf`	Temporally Disentangled Representation Learning under Unknown Nonstationarity. NeurIPS Xiangchen Song, Weiran Yao, Yewen Fan, Xinshuai Dong, Guangyi Chen, Juan Carlos Niebles, Eric P. Xing, Kun Zhang
2023	J	`jnl`	Temporally Disentangled Representation Learning under Unknown Nonstationarity. CoRR Xiangchen Song, Weiran Yao, Yewen Fan, Xinshuai Dong, Guangyi Chen, Juan Carlos Niebles, Eric P. Xing, Kun Zhang
2023	A*	`conf`	Understanding Masked Autoencoders via Hierarchical Latent Variable Models. CVPR Lingjing Kong, Martin Q. Ma, Guangyi Chen, Eric P. Xing, Yuejie Chi, Louis-Philippe Morency, Kun Zhang
2023	J	`jnl`	Understanding Masked Autoencoders via Hierarchical Latent Variable Models. CoRR Lingjing Kong, Martin Q. Ma, Guangyi Chen, Eric P. Xing, Yuejie Chi, Louis-Philippe Morency, Kun Zhang
2023	A*	`conf`	Weakly Supervised 3D Open-vocabulary Segmentation. NeurIPS Kunhao Liu, Fangneng Zhan, Jiahui Zhang, Muyu Xu, Yingchen Yu, Abdulmotaleb El Saddik, Christian Theobalt, Eric P. Xing, Shijian Lu
2022	—	`conf`	A Fast Knowledge Distillation Framework for Visual Recognition. ECCV (24) Zhiqiang Shen, Eric P. Xing
2022	A*	`conf`	AMP: Automatically Finding Model Parallel Strategies with Heterogeneity Awareness. NeurIPS Dacheng Li, Hongyi Wang, Eric P. Xing, Hao Zhang
2022	J	`jnl`	AMP: Automatically Finding Model Parallel Strategies with Heterogeneity Awareness. CoRR Dacheng Li, Hongyi Wang, Eric P. Xing, Hao Zhang
2022	—	`conf`	ASDOT: Any-Shot Data-to-Text Generation with Pretrained Language Models. EMNLP (Findings) Jiannan Xiang, Zhengzhong Liu, Yucheng Zhou, Eric P. Xing, Zhiting Hu
2022	J	`jnl`	ASDOT: Any-Shot Data-to-Text Generation with Pretrained Language Models. CoRR Jiannan Xiang, Zhengzhong Liu, Yucheng Zhou, Eric P. Xing, Zhiting Hu
2022	A*	`conf`	Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep Learning. OSDI Lianmin Zheng, Zhuohan Li, Hao Zhang, Yonghao Zhuang, Zhifeng Chen, Yanping Huang, Yida Wang, Yuanzhong Xu, Danyang Zhuo, Eric P. Xing, Joseph E. Gonzalez, Ion Stoica
2022	J	`jnl`	BertNet: Harvesting Knowledge Graphs from Pretrained Language Models. CoRR Shibo Hao, Bowen Tan, Kaiwen Tang, Hengzhe Zhang, Eric P. Xing, Zhiting Hu
2022	J	`jnl`	Betty: An Automatic Differentiation Library for Multilevel Optimization. CoRR Sang Keun Choe, Willie Neiswanger, Pengtao Xie, Eric P. Xing
2022	J	`jnl`	Can Transformers be Strong Treatment Effect Estimators? CoRR Yifan Zhang, Hanlin Zhang, Zachary C. Lipton, Li Erran Li, Eric P. Xing
2022	J	`jnl`	DNB: A Joint Learning Framework for Deep Bayesian Nonparametric Clustering. IEEE Trans. Neural Networks Learn. Syst. Zeya Wang, Yang Ni, Baoyu Jing, Deqing Wang, Hao Zhang, Eric P. Xing
2022	—	`conf`	Data-Free Neural Architecture Search via Recursive Label Calibration. ECCV (24) Zechun Liu, Zhiqiang Shen, Yun Long, Eric P. Xing, Kwang-Ting Cheng, Chas Leichner
2022	A	`conf`	Dropout as a Regularizer of Interaction Effects. AISTATS Benjamin J. Lengerich, Eric P. Xing, Rich Caruana
2022	—	`conf`	Efficient (Soft) Q-Learning for Text Generation with Limited Good Data. EMNLP (Findings) Han Guo, Bowen Tan, Zhengzhong Liu, Eric P. Xing, Zhiting Hu
2022	J	`jnl`	Expeditious Saliency-guided Mix-up through Random Gradient Thresholding. CoRR Minh-Long Luu, Zeyi Huang, Eric P. Xing, Yong Jae Lee, Haohan Wang
2022	B	`conf`	Gene Set Priorization Guided by Regulatory Networks with p-values through Kernel Mixed Model. RECOMB Haohan Wang, Oscar L. Lopez, Wei Wu, Eric P. Xing
2022	J	`jnl`	Kernel Mixed Model for Transcriptome Association Study. J. Comput. Biol. Haohan Wang, Oscar Lopez, Eric P. Xing, Wei Wu
2022	A*	`conf`	Learning from Mistakes - a Framework for Neural Architecture Search. AAAI Bhanu Garg, Li Zhang, Pradyumna Sridhara, Ramtin Hosseini, Eric P. Xing, Pengtao Xie
2022	J	`jnl`	MPCFormer: fast, performant and private Transformer inference with MPC. CoRR Dacheng Li, Rulin Shao, Hongyi Wang, Han Guo, Eric P. Xing, Hao Zhang
2022	J	`jnl`	MRCLens: an MRC Dataset Bias Detection Toolkit. CoRR Yifan Zhong, Haohan Wang, Eric P. Xing
2022	A*	`conf`	Masked Generative Adversarial Networks are Data-Efficient Generation Learners. NeurIPS Jiaxing Huang, Kaiwen Cui, Dayan Guan, Aoran Xiao, Fangneng Zhan, Shijian Lu, Shengcai Liao, Eric P. Xing
2022	J	`jnl`	Meta-DETR: Image-Level Few-Shot Detection with Inter-Class Correlation Exploitation. CoRR Gongjie Zhang, Zhipeng Luo, Kaiwen Cui, Shijian Lu, Eric P. Xing
2022	J	`jnl`	MixMask: Revisiting Masked Siamese Self-supervised Learning in Asymmetric Distance. CoRR Kirill Vishniakov, Eric P. Xing, Zhiqiang Shen
2022	J	`jnl`	Negational symmetry of quantum neural networks for binary pattern classification. Pattern Recognit. Nanqing Dong, Michael Kampffmeyer, Irina Voiculescu, Eric P. Xing
2022	A*	`conf`	Nonuniform-to-Uniform Quantization: Towards Accurate Quantization via Generalized Straight-Through Estimation. CVPR Zechun Liu, Kwang-Ting Cheng, Dong Huang, Eric P. Xing, Zhiqiang Shen
2022	J	`jnl`	On Optimizing the Communication of Model Parallelism. CoRR Yonghao Zhuang, Hexu Zhao, Lianmin Zheng, Zhuohan Li, Eric P. Xing, Qirong Ho, Joseph E. Gonzalez, Ion Stoica, Hao Zhang
2022	J	`jnl`	RLPrompt: Optimizing Discrete Text Prompts With Reinforcement Learning. CoRR Mingkai Deng, Jianyu Wang, Cheng-Ping Hsieh, Yihan Wang, Han Guo, Tianmin Shu, Meng Song, Eric P. Xing, Zhiting Hu
2022	A*	`conf`	RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning. EMNLP Mingkai Deng, Jianyu Wang, Cheng-Ping Hsieh, Yihan Wang, Han Guo, Tianmin Shu, Meng Song, Eric P. Xing, Zhiting Hu
2022	A*	`conf`	Rare Gems: Finding Lottery Tickets at Initialization. NeurIPS Kartik Sreenivasan, Jy-yong Sohn, Liu Yang, Matthew Grinde, Alliot Nagle, Hongyi Wang, Eric P. Xing, Kangwook Lee, Dimitris S. Papailiopoulos
2022	J	`jnl`	Robustar: Interactive Toolbox Supporting Precise Data Annotation for Robust Vision Learning. CoRR Chonghan Chen, Haohan Wang, Leyang Hu, Yuhao Zhang, Shuguang Lyu, Jingcheng Wu, Xinnuo Li, Linjing Sun, Eric P. Xing
2022	A*	`conf`	SDQ: Stochastic Differentiable Quantization with Mixed Precision. ICML Xijie Huang, Zhiqiang Shen, Shichao Li, Zechun Liu, Xianghong Hu, Jeffry Wicaksana, Eric P. Xing, Kwang-Ting Cheng
2022	J	`jnl`	SDQ: Stochastic Differentiable Quantization with Mixed Precision. CoRR Xijie Huang, Zhiqiang Shen, Shichao Li, Zechun Liu, Xianghong Hu, Jeffry Wicaksana, Eric P. Xing, Kwang-Ting Cheng
2022	J	`jnl`	Semantic-Aligned Matching for Enhanced DETR Convergence and Multi-Scale Feature Fusion. CoRR Gongjie Zhang, Zhipeng Luo, Yingchen Yu, Jiaxing Huang, Kaiwen Cui, Shijian Lu, Eric P. Xing
2022	—	`conf`	Sliced Recursive Transformer. ECCV (24) Zhiqiang Shen, Zechun Liu, Eric P. Xing
2022	J	`jnl`	Stochastic Neural Networks with Infinite Width are Deterministic. CoRR Liu Ziyin, Hanlin Zhang, Xiangming Meng, Yuting Lu, Eric P. Xing, Masahito Ueda
2022	J	`jnl`	The Impact of Symbolic Representations on In-context Learning for Few-shot Reasoning. CoRR Hanlin Zhang, Yifan Zhang, Li Erran Li, Eric P. Xing
2022	A*	`conf`	The Two Dimensions of Worst-case Training and Their Integrated Effect for Out-of-domain Generalization. CVPR Zeyi Huang, Haohan Wang, Dong Huang, Yong Jae Lee, Eric P. Xing
2022	J	`jnl`	The Two Dimensions of Worst-case Training and the Integrated Effect for Out-of-domain Generalization. CoRR Zeyi Huang, Haohan Wang, Dong Huang, Yong Jae Lee, Eric P. Xing
2022	A*	`conf`	Toward Learning Robust and Invariant Representations with Alignment Regularization and Data Augmentation. KDD Haohan Wang, Zeyi Huang, Xindi Wu, Eric P. Xing
2022	J	`jnl`	Toward Learning Robust and Invariant Representations with Alignment Regularization and Data Augmentation. CoRR Haohan Wang, Zeyi Huang, Xindi Wu, Eric P. Xing
2022	A	`conf`	Toward learning human-aligned cross-domain robust models by countering misaligned features. UAI Haohan Wang, Zeyi Huang, Hanlin Zhang, Yong Jae Lee, Eric P. Xing
2022	A*	`conf`	Towards Principled Disentanglement for Domain Generalization. CVPR Hanlin Zhang, Yifan Zhang, Weiyang Liu, Adrian Weller, Bernhard Schölkopf, Eric P. Xing
2022	J	`jnl`	Towards robust partially supervised multi-structure medical image segmentation on small-scale data. Appl. Soft Comput. Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang, Min Xu, Irina Voiculescu, Eric P. Xing
2022	J	`jnl`	Trade-offs of Linear Mixed Models in Genome-Wide Association Studies. J. Comput. Biol. Haohan Wang, Bryon Aragam, Eric P. Xing
2022	A*	`conf`	Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space. CVPR Arnav Chavan, Zhiqiang Shen, Zhuang Liu, Zechun Liu, Kwang-Ting Cheng, Eric P. Xing
2022	J	`jnl`	Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space. CoRR Arnav Chavan, Zhiqiang Shen, Zhuang Liu, Zechun Liu, Kwang-Ting Cheng, Eric P. Xing
2021	J	`jnl`	A Data-Centric Framework for Composable NLP Workflows. CoRR Zhengzhong Liu, Guanxiong Ding, Avinash Bukkittu, Mansi Gupta, Pengzhi Gao, Atif Ahmed, Shikun Zhang, Xin Gao, Swapnil Singhavi, Linwei Li, Wei Wei, Zecong Hu, Haoran Shi, Xiaodan Liang, Teruko Mitamura, Eric P. Xing, Zhiting Hu
2021	J	`jnl`	A Fast Knowledge Distillation Framework for Visual Recognition. CoRR Zhiqiang Shen, Eric P. Xing
2021	J	`jnl`	Active learning to classify macromolecular structures in situ for less supervision in cryo-electron tomography. Bioinform. Xuefeng Du, Haohan Wang, Zhenxi Zhu, Xiangrui Zeng, Yi-Wei Chang, Jing Zhang, Eric P. Xing, Min Xu
2021	J	`jnl`	Amortized Auto-Tuning: Cost-Efficient Transfer Optimization for Hyperparameter Recommendation. CoRR Yuxin Xiao, Eric P. Xing, Willie Neiswanger
2021	—	`conf`	Compression, Transduction, and Creation: A Unified Framework for Evaluating Natural Language Generation. EMNLP (1) Mingkai Deng, Bowen Tan, Zhengzhong Liu, Eric P. Xing, Zhiting Hu
2021	J	`jnl`	Compression, Transduction, and Creation: A Unified Framework for Evaluating Natural Language Generation. CoRR Mingkai Deng, Bowen Tan, Zhengzhong Liu, Eric P. Xing, Zhiting Hu
2021	J	`jnl`	Cooperative Multi-Agent Actor-Critic for Privacy-Preserving Load Scheduling in a Residential Microgrid. CoRR Zhaoming Qin, Nanqing Dong, Eric P. Xing, Junwei Cao
2021	J	`jnl`	Coupled mixed model for joint genetic analysis of complex disorders with two independently collected data sets. BMC Bioinform. Haohan Wang, Fen Pei, Michael M. Vanyukov, Ivet Bahar, Wei Wu, Eric P. Xing
2021	J	`jnl`	Data-Free Neural Architecture Search via Recursive Label Calibration. CoRR Zechun Liu, Zhiqiang Shen, Yun Long, Eric P. Xing, Kwang-Ting Cheng, Chas Leichner
2021	A*	`conf`	Explaining A Black-box By Using A Deep Variational Information Bottleneck Approach. AAAI Seo-Jin Bang, Pengtao Xie, Heewook Lee, Wei Wu, Eric P. Xing
2021	A*	`conf`	Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms. ICLR Maruan Al-Shedivat, Jennifer Gillenwater, Eric P. Xing, Afshin Rostamizadeh
2021	—	`conf`	GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning. ACL/IJCNLP (Findings) Jiaqi Chen, Jianheng Tang, Jinghui Qin, Xiaodan Liang, Lingbo Liu, Eric P. Xing, Liang Lin
2021	J	`jnl`	GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning. CoRR Jiaqi Chen, Jianheng Tang, Jinghui Qin, Xiaodan Liang, Lingbo Liu, Eric P. Xing, Liang Lin
2021	A*	`conf`	Interactive Weak Supervision: Learning Useful Heuristics for Data Labeling. ICLR Benedikt Boecking, Willie Neiswanger, Eric P. Xing, Artur Dubrawski
2021	—	`conf`	Knowledge-Aware Meta-learning for Low-Resource Text Classification. EMNLP (1) Huaxiu Yao, Yingxin Wu, Maruan Al-Shedivat, Eric P. Xing
2021	J	`jnl`	Knowledge-Aware Meta-learning for Low-Resource Text Classification. CoRR Huaxiu Yao, Yingxin Wu, Maruan Al-Shedivat, Eric P. Xing
2021	J	`jnl`	Learning from Mistakes - A Framework for Neural Architecture Search. CoRR Bhanu Garg, Li Zhang, Pradyumna Sridhara, Ramtin Hosseini, Eric P. Xing, Pengtao Xie
2021	J	`jnl`	Multi-modal Self-supervised Pre-training for Regulatory Genome Across Cell Types. CoRR Shentong Mo, Xi Fu, Chenyang Hong, Yizhen Chen, Yuxuan Zheng, Xiangru Tang, Zhiqiang Shen, Eric P. Xing, Yanyan Lan
2021	A*	`conf`	Multi-task Learning of Order-Consistent Causal Graphs. NeurIPS Xinshi Chen, Haoran Sun, Caleb Ellington, Eric P. Xing, Le Song
2021	J	`jnl`	Multi-task Learning of Order-Consistent Causal Graphs. CoRR Xinshi Chen, Haoran Sun, Caleb Ellington, Eric P. Xing, Le Song
2021	J	`jnl`	NOTMAD: Estimating Bayesian Networks with Sample-Specific Structures and Parameters. CoRR Benjamin J. Lengerich, Caleb Ellington, Bryon Aragam, Eric P. Xing, Manolis Kellis
2021	J	`jnl`	Negational Symmetry of Quantum Neural Networks for Binary Pattern Classification. CoRR Nanqing Dong, Michael Kampffmeyer, Irina Voiculescu, Eric P. Xing
2021	J	`jnl`	Nonuniform-to-Uniform Quantization: Towards Accurate Quantization via Generalized Straight-Through Estimation. CoRR Zechun Liu, Kwang-Ting Cheng, Dong Huang, Eric P. Xing, Zhiqiang Shen
2021	A	`conf`	On Data Efficiency of Meta-learning. AISTATS Maruan Al-Shedivat, Liam Li, Eric P. Xing, Ameet Talwalkar
2021	—	`conf`	On the Generation of Medical Dialogs for COVID-19. ACL/IJCNLP (2) Meng Zhou, Zechen Li, Bowen Tan, Guangtao Zeng, Wenmian Yang, Xuehai He, Zeqian Ju, Subrato Chakravorty, Shu Chen, Xingyi Yang, Yichen Zhang, Qingyang Wu, Zhou Yu, Kun Xu, Eric P. Xing, Pengtao Xie
2021	J	`jnl`	Panoramic Learning with A Standardized Machine Learning Formalism. CoRR Zhiting Hu, Eric P. Xing
2021	A*	`conf`	Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning. OSDI Aurick Qiao, Sang Keun Choe, Suhas Jayaram Subramanya, Willie Neiswanger, Qirong Ho, Hao Zhang, Gregory R. Ganger, Eric P. Xing
2021	—	`conf`	Progressive Generation of Long Text with Pretrained Language Models. NAACL-HLT Bowen Tan, Zichao Yang, Maruan Al-Shedivat, Eric P. Xing, Zhiting Hu
2021	J	`jnl`	Prototypical Graph Contrastive Learning. CoRR Shuai Lin, Pan Zhou, Zi-Yuan Hu, Shuojia Wang, Ruihui Zhao, Yefeng Zheng, Liang Lin, Eric P. Xing, Xiaodan Liang
2021	J	`jnl`	Sliced Recursive Transformer. CoRR Zhiqiang Shen, Zechun Liu, Eric P. Xing
2021	J	`jnl`	Supervised Adversarial Alignment of Single-Cell RNA-seq Data. J. Comput. Biol. Songwei Ge, Haohan Wang, Amir Alavi, Eric P. Xing, Ziv Bar-Joseph
2021	J	`jnl`	Technology Readiness Levels for Machine Learning Systems. CoRR Alexander Lavin, Ciarán M. Gilligan-Lee, Alessya Visnjic, Siddha Ganju, Dava J. Newman, Sujoy Ganguly, Danny Lange, Atilim Günes Baydin, Amit Sharma, Adam Gibson, Yarin Gal, Eric P. Xing, Chris Mattmann, James Parr
2021	J	`jnl`	Text Generation with Efficient (Soft) Q-Learning. CoRR Han Guo, Bowen Tan, Zhengzhong Liu, Eric P. Xing, Zhiting Hu
2021	J	`jnl`	Towards Principled Disentanglement for Domain Generalization. CoRR Hanlin Zhang, Yifan Zhang, Weiyang Liu, Adrian Weller, Bernhard Schölkopf, Eric P. Xing
2021	—	`conf`	Towards Visual Question Answering on Pathology Images. ACL/IJCNLP (2) Xuehai He, Zhuo Cai, Wenlan Wei, Yichen Zhang, Luntian Mou, Eric P. Xing, Pengtao Xie
2021	J	`jnl`	Tradeoffs of Linear Mixed Models in Genome-wide Association Studies. CoRR Haohan Wang, Bryon Aragam, Eric P. Xing
2020	—	`conf`	A Data-Centric Framework for Composable NLP Workflows. EMNLP (Demos) Zhengzhong Liu, Guanxiong Ding, Avinash Bukkittu, Mansi Gupta, Pengzhi Gao, Atif Ahmed, Shikun Zhang, Xin Gao, Swapnil Singhavi, Linwei Li, Wei Wei, Zecong Hu, Haoran Shi, Xiaodan Liang, Teruko Mitamura, Eric P. Xing, Zhiting Hu
2020	A	`conf`	Adversarial Domain Adaptation Being Aware of Class Relationships. ECAI Zeya Wang, Baoyu Jing, Yang Ni, Nanqing Dong, Pengtao Xie, Eric P. Xing
2020	A*	`conf`	AutoSync: Learning to Synchronize for Data-Parallel Distributed Deep Learning. NeurIPS Hao Zhang, Yuan Li, Zhijie Deng, Xiaodan Liang, Lawrence Carin, Eric P. Xing
2020	A	`conf`	ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations. AISTATS Ksenia Korovina, Sailun Xu, Kirthevasan Kandasamy, Willie Neiswanger, Barnabás Póczos, Jeff Schneider, Eric P. Xing
2020	J	`jnl`	Contextual Explanation Networks. J. Mach. Learn. Res. Maruan Al-Shedivat, Avinava Dubey, Eric P. Xing
2020	A	`conf`	Distributed, partially collapsed MCMC for Bayesian Nonparametrics. AISTATS Kumar Avinava Dubey, Michael Minyi Zhang, Eric P. Xing, Sinead Williamson
2020	J	`jnl`	Distributed, partially collapsed MCMC for Bayesian Nonparametrics. CoRR Avinava Dubey, Michael Minyi Zhang, Eric P. Xing, Sinead A. Williamson
2020	J	`jnl`	Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms. CoRR Maruan Al-Shedivat, Jennifer Gillenwater, Eric P. Xing, Afshin Rostamizadeh
2020	A*	`conf`	Generalized Zero-Shot Text Classification for ICD Coding. IJCAI Congzheng Song, Shanghang Zhang, Najmeh Sadoughi, Pengtao Xie, Eric P. Xing
2020	A*	`conf`	High-Frequency Component Helps Explain the Generalization of Convolutional Neural Networks. CVPR Haohan Wang, Xindi Wu, Zeyi Huang, Eric P. Xing
2020	A*	`conf`	Improving GAN Training with Probability Ratio Clipping and Sample Reweighting. NeurIPS Yue Wu, Pan Zhou, Andrew Gordon Wilson, Eric P. Xing, Zhiting Hu
2020	J	`jnl`	Improving GAN Training with Probability Ratio Clipping and Sample Reweighting. CoRR Yue Wu, Pan Zhou, Andrew Gordon Wilson, Eric P. Xing, Zhiting Hu
2020	J	`jnl`	Iterative Graph Self-Distillation. CoRR Hanlin Zhang, Shuai Lin, Weiyang Liu, Pan Zhou, Jian Tang, Xiaodan Liang, Eric P. Xing
2020	A	`conf`	Learning Sparse Nonparametric DAGs. AISTATS Xun Zheng, Chen Dan, Bryon Aragam, Pradeep Ravikumar, Eric P. Xing
2020	A*	`conf`	Learning from All Types of Experiences: A Unifying Machine Learning Perspective. KDD Zhiting Hu, Eric P. Xing
2020	J	`jnl`	Learning from Imperfect Annotations. CoRR Emmanouil Antonios Platanios, Maruan Al-Shedivat, Eric P. Xing, Tom M. Mitchell
2020	J	`jnl`	Methods for comparing uncertainty quantifications for material property predictions. Mach. Learn. Sci. Technol. Kevin Tran, Willie Neiswanger, Junwoong Yoon, Qingyang Zhang, Eric P. Xing, Zachary W. Ulissi
2020	J	`jnl`	On Dropout, Overfitting, and Interaction Effects in Deep Neural Networks. CoRR Benjamin J. Lengerich, Eric P. Xing, Rich Caruana
2020	J	`jnl`	On the Generation of Medical Dialogues for COVID-19. CoRR Wenmian Yang, Guangtao Zeng, Bowen Tan, Zeqian Ju, Subrato Chakravorty, Xuehai He, Shu Chen, Xingyi Yang, Qingyang Wu, Zhou Yu, Eric P. Xing, Pengtao Xie
2020	J	`jnl`	PathVQA: 30000+ Questions for Medical Visual Question Answering. CoRR Xuehai He, Yichen Zhang, Luntian Mou, Eric P. Xing, Pengtao Xie
2020	J	`jnl`	Pathological Visual Question Answering. CoRR Xuehai He, Zhuo Cai, Wenlan Wei, Yichen Zhang, Luntian Mou, Eric P. Xing, Pengtao Xie
2020	J	`jnl`	Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning. CoRR Aurick Qiao, Willie Neiswanger, Qirong Ho, Hao Zhang, Gregory R. Ganger, Eric P. Xing
2020	J	`jnl`	Poly(A)-DG: A deep-learning-based domain generalization method to identify cross-species Poly(A) signal without prior knowledge from target species. PLoS Comput. Biol. Yumin Zheng, Haohan Wang, Yang Zhang, Xin Gao, Eric P. Xing, Min Xu
2020	J	`jnl`	Progressive Generation of Long Text. CoRR Bowen Tan, Zichao Yang, Maruan Al-Shedivat, Eric P. Xing, Zhiting Hu
2020	—	`conf`	Record-to-Text Generation with Style Imitation. EMNLP (Findings) Shuai Lin, Wentao Wang, Zichao Yang, Xiaodan Liang, Frank F. Xu, Eric P. Xing, Zhiting Hu
2020	A*	`conf`	Regularizing Black-box Models for Improved Interpretability. NeurIPS Gregory Plumb, Maruan Al-Shedivat, Ángel Alexander Cabrera, Adam Perer, Eric P. Xing, Ameet Talwalkar
2020	J	`jnl`	Self-Challenging Improves Cross-Domain Generalization. CoRR Zeyi Huang, Haohan Wang, Eric P. Xing, Dong Huang
2020	—	`conf`	Self-challenging Improves Cross-Domain Generalization. ECCV (2) Zeyi Huang, Haohan Wang, Eric P. Xing, Dong Huang
2020	J	`jnl`	Show, Describe and Conclude: On Exploiting the Structure Information of Chest X-Ray Reports. CoRR Baoyu Jing, Zeya Wang, Eric P. Xing
2020	J	`jnl`	Squared 𝓁 CoRR Haohan Wang, Zeyi Huang, Xindi Wu, Eric P. Xing
2020	—	`conf`	Summarizing Text on Any Aspects: A Knowledge-Informed Weakly-Supervised Approach. EMNLP (1) Bowen Tan, Lianhui Qin, Eric P. Xing, Zhiting Hu
2020	J	`jnl`	Summarizing Text on Any Aspects: A Knowledge-Informed Weakly-Supervised Approach. CoRR Bowen Tan, Lianhui Qin, Eric P. Xing, Zhiting Hu
2020	B	`conf`	Supervised Adversarial Alignment of Single-Cell RNA-seq Data. RECOMB Songwei Ge, Haohan Wang, Amir Alavi, Eric P. Xing, Ziv Bar-Joseph
2020	J	`jnl`	Towards Robust Medical Image Segmentation on Small-Scale Data with Incomplete Labels. CoRR Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang, Min Xu, Irina Voiculescu, Eric P. Xing
2020	J	`jnl`	Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly. J. Mach. Learn. Res. Kirthevasan Kandasamy, Karun Raju Vysyaraju, Willie Neiswanger, Biswajit Paria, Christopher R. Collins, Jeff Schneider, Barnabás Póczos, Eric P. Xing
2020	J	`jnl`	Unsupervised object-level video summarization with online motion auto-encoder. Pattern Recognit. Lett. Yujia Zhang, Xiaodan Liang, Dingwen Zhang, Min Tan, Eric P. Xing
2020	J	`jnl`	Validate and Enable Machine Learning in Industrial AI. CoRR Hongbo Zou, Guangjing Chen, Pengtao Xie, Sean Chen, Yongtian He, Hochih Huang, Zheng Nie, Hongbao Zhang, Tristan Bala, Kazi Tulip, Yuqi Wang, Shenlin Qin, Eric P. Xing
2020	J	`jnl`	WGAN domain adaptation for the joint optic disc-and-cup segmentation in fundus images. Int. J. Comput. Assist. Radiol. Surg. Shreya Kadambi, Zeya Wang, Eric P. Xing
2020	J	`jnl`	Word Shape Matters: Robust Machine Translation with Visual Embedding. CoRR Haohan Wang, Peiyan Zhang, Eric P. Xing
2020	J	`jnl`	XRayGAN: Consistency-preserving Generation of X-ray Images from Radiology Reports. CoRR Xingyi Yang, Nandiraju Gireesh, Eric P. Xing, Pengtao Xie
2019	J	`jnl`	Adversarial Domain Adaptation Being Aware of Class Relationships. CoRR Zeya Wang, Baoyu Jing, Yang Ni, Nanqing Dong, Pengtao Xie, Eric P. Xing
2019	—	`conf`	AutoLoss: Learning Discrete Schedule for Alternate Optimization. ICLR (Poster) Haowen Xu, Hao Zhang, Zhiting Hu, Xiaodan Liang, Ruslan Salakhutdinov, Eric P. Xing
2019	Misc	`conf`	Automatic Human-like Mining and Constructing Reliable Genetic Association Database with Deep Reinforcement Learning. PSB Haohan Wang, Xiang Liu, Yifeng Tao, Wenting Ye, Qiao Jin, William W. Cohen, Eric P. Xing
2019	A	`conf`	Automating Dependence-Aware Parallelization of Machine Learning Training on Distributed Shared Memory. EuroSys Jinliang Wei, Garth A. Gibson, Phillip B. Gibbons, Eric P. Xing
2019	J	`jnl`	ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations. CoRR Ksenia Korovina, Sailun Xu, Kirthevasan Kandasamy, Willie Neiswanger, Barnabás Póczos, Jeff Schneider, Eric P. Xing
2019	J	`jnl`	ConnNet: A Long-Range Relation-Aware Pixel-Connectivity Network for Salient Segmentation. IEEE Trans. Image Process. Michael Kampffmeyer, Nanqing Dong, Xiaodan Liang, Yujia Zhang, Eric P. Xing
2019	—	`conf`	Connecting the Dots Between MLE and RL for Sequence Generation. DeepRLStructPred@ICLR Bowen Tan, Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, Eric P. Xing
2019	—	`conf`	Deep Inductive Matrix Completion for Biomedical Interaction Prediction. BIBM Haohan Wang, Yibing Wei, Mengxin Cao, Ming Xu, Wei Wu, Eric P. Xing
2019	J	`jnl`	Deep mixed model for marginal epistasis detection and population stratification correction in genome-wide association studies. BMC Bioinform. Haohan Wang, Tianwei Yue, Jingkang Yang, Wei Wu, Eric P. Xing
2019	J	`jnl`	Dilated temporal relational adversarial network for generic video summarization. Multim. Tools Appl. Yujia Zhang, Michael Kampffmeyer, Xiaodan Liang, Dingwen Zhang, Min Tan, Eric P. Xing
2019	J	`jnl`	Discourse in Multimedia: A Case Study in Extracting Geometry Knowledge from Textbooks. Comput. Linguistics Mrinmaya Sachan, Avinava Dubey, Eduard H. Hovy, Tom M. Mitchell, Dan Roth, Eric P. Xing
2019	J	`jnl`	Efficient Exploration via State Marginal Matching. CoRR Lisa Lee, Benjamin Eysenbach, Emilio Parisotto, Eric P. Xing, Sergey Levine, Ruslan Salakhutdinov
2019	—	`conf`	Ellipse Detection of Optic Disc-and-Cup Boundary in Fundus Images. ISBI Zeya Wang, Nanqing Dong, Sean D. Rosario, Min Xu, Pengtao Xie, Eric P. Xing
2019	J	`jnl`	Explaining a black-box using Deep Variational Information Bottleneck Approach. CoRR Seo-Jin Bang, Pengtao Xie, Wei Wu, Eric P. Xing
2019	A*	`conf`	Fault Tolerance in Iterative-Convergent Machine Learning. ICML Aurick Qiao, Bryon Aragam, Bingjing Zhang, Eric P. Xing
2019	J	`jnl`	Generalized Zero-shot ICD Coding. CoRR Congzheng Song, Shanghang Zhang, Najmeh Sadoughi, Pengtao Xie, Eric P. Xing
2019	—	`conf`	Graph-structured Sparse Mixed Models for Genetic Association with Confounding Factors Correction. BIBM Haohan Wang, Changpeng Lu, Wei Wu, Eric P. Xing
2019	J	`jnl`	High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks. CoRR Haohan Wang, Xindi Wu, Pengcheng Yin, Eric P. Xing
2019	A*	`conf`	Knowledge-Driven Encode, Retrieve, Paraphrase for Medical Image Report Generation. AAAI Christy Y. Li, Xiaodan Liang, Zhiting Hu, Eric P. Xing
2019	J	`jnl`	Knowledge-driven Encode, Retrieve, Paraphrase for Medical Image Report Generation. CoRR Christy Y. Li, Xiaodan Liang, Zhiting Hu, Eric P. Xing
2019	A*	`conf`	Learning Data Manipulation for Augmentation and Weighting. NeurIPS Zhiting Hu, Bowen Tan, Ruslan Salakhutdinov, Tom M. Mitchell, Eric P. Xing
2019	J	`jnl`	Learning Data Manipulation for Augmentation and Weighting. CoRR Zhiting Hu, Bowen Tan, Ruslan Salakhutdinov, Tom M. Mitchell, Eric P. Xing
2019	A*	`conf`	Learning Robust Global Representations by Penalizing Local Predictive Power. NeurIPS Haohan Wang, Songwei Ge, Zachary C. Lipton, Eric P. Xing
2019	J	`jnl`	Learning Robust Global Representations by Penalizing Local Predictive Power. CoRR Haohan Wang, Songwei Ge, Eric P. Xing, Zachary C. Lipton
2019	—	`conf`	Learning Robust Representations by Projecting Superficial Statistics Out. ICLR Haohan Wang, Zexue He, Zachary C. Lipton, Eric P. Xing
2019	J	`jnl`	Learning Robust Representations by Projecting Superficial Statistics Out. CoRR Haohan Wang, Zexue He, Zachary C. Lipton, Eric P. Xing
2019	A*	`conf`	Learning Sample-Specific Models with Low-Rank Personalized Regression. NeurIPS Benjamin J. Lengerich, Bryon Aragam, Eric P. Xing
2019	J	`jnl`	Learning Sample-Specific Models with Low-Rank Personalized Regression. CoRR Benjamin J. Lengerich, Bryon Aragam, Eric P. Xing
2019	J	`jnl`	Learning Sparse Nonparametric DAGs. CoRR Xun Zheng, Chen Dan, Bryon Aragam, Pradeep Ravikumar, Eric P. Xing
2019	—	`conf`	Multimodal Machine Learning for Automated ICD Coding. MLHC Keyang Xu, Mike Lam, Jingzhi Pang, Xin Gao, Charlotte Band, Piyush Mathur, Frank Papay, Ashish K. Khanna, Jacek B. Cywinski, Kamal Maheshwari, Pengtao Xie, Eric P. Xing
2019	—	`conf`	Neural Architecture Search for Adversarial Medical Image Segmentation. MICCAI (6) Nanqing Dong, Min Xu, Xiaodan Liang, Yiliang Jiang, Wei Dai, Eric P. Xing
2019	J	`jnl`	Precision Lasso: accounting for correlations and linear dependencies in high-dimensional genomic data. Bioinform. Haohan Wang, Benjamin J. Lengerich, Bryon Aragam, Eric P. Xing
2019	J	`jnl`	ProBO: a Framework for Using Probabilistic Programming in Bayesian Optimization. CoRR Willie Neiswanger, Kirthevasan Kandasamy, Barnabás Póczos, Jeff Schneider, Eric P. Xing
2019	—	`conf`	Regularized Adversarial Training (RAT) for Robust Cellular Electron Cryo Tomograms Classification. BIBM Xindi Wu, Yijun Mao, Haohan Wang, Xiangrui Zeng, Xin Gao, Eric P. Xing, Min Xu
2019	J	`jnl`	Regularizing Black-box Models for Improved Interpretability (HILL 2019 Version). CoRR Gregory Plumb, Maruan Al-Shedivat, Eric P. Xing, Ameet Talwalkar
2019	J	`jnl`	Regularizing Black-box Models for Improved Interpretability. CoRR Gregory Plumb, Maruan Al-Shedivat, Eric P. Xing, Ameet Talwalkar
2019	Misc	`conf`	Removing Confounding Factors Associated Weights in Deep Neural Networks Improves the Prediction Accuracy for Healthcare Applications. PSB Haohan Wang, Zhenglin Wu, Eric P. Xing
2019	A*	`conf`	Rethinking Knowledge Graph Propagation for Zero-Shot Learning. CVPR Michael Kampffmeyer, Yinbo Chen, Xiaodan Liang, Hao Wang, Yujia Zhang, Eric P. Xing
2019	—	`conf`	STRADS-AP: Simplifying Distributed Machine Learning Programming without Introducing a New Programming Model. USENIX ATC Jin Kyu Kim, Abutalib Aghayev, Garth A. Gibson, Eric P. Xing
2019	—	`conf`	Show, Describe and Conclude: On Exploiting the Structure Information of Chest X-ray Reports. ACL (1) Baoyu Jing, Zeya Wang, Eric P. Xing
2019	A*	`conf`	Specific and Shared Causal Relation Modeling and Mechanism-Based Clustering. NeurIPS Biwei Huang, Kun Zhang, Pengtao Xie, Mingming Gong, Eric P. Xing, Clark Glymour
2019	J	`jnl`	SysML: The New Frontier of Machine Learning Systems. CoRR Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric S. Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros G. Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim M. Hazelwood, Furong Huang, Martin Jaggi, Kevin Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konecný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Gordon Murray, Dimitris S. Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan Randall Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric P. Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar
2019	—	`conf`	Target-Guided Open-Domain Conversation. ACL (1) Jianheng Tang, Tiancheng Zhao, Chenyan Xiong, Xiaodan Liang, Eric P. Xing, Zhiting Hu
2019	J	`jnl`	Target-Guided Open-Domain Conversation. CoRR Jianheng Tang, Tiancheng Zhao, Chenyan Xiong, Xiaodan Liang, Eric P. Xing, Zhiting Hu
2019	—	`conf`	Texar: A Modularized, Versatile, and Extensible Toolkit for Text Generation. ACL (3) Zhiting Hu, Haoran Shi, Bowen Tan, Wentao Wang, Zichao Yang, Tiancheng Zhao, Junxian He, Lianhui Qin, Di Wang, Xuezhe Ma, Zhengzhong Liu, Xiaodan Liang, Wanrong Zhu, Devendra Singh Sachan, Eric P. Xing
2019	J	`jnl`	Text Infilling. CoRR Wanrong Zhu, Zhiting Hu, Eric P. Xing
2019	A*	`conf`	Theoretically Principled Trade-off between Robustness and Accuracy. ICML Hongyang Zhang, Yaodong Yu, Jiantao Jiao, Eric P. Xing, Laurent El Ghaoui, Michael I. Jordan
2019	J	`jnl`	Theoretically Principled Trade-off between Robustness and Accuracy. CoRR Hongyang Zhang, Yaodong Yu, Jiantao Jiao, Eric P. Xing, Laurent El Ghaoui, Michael I. Jordan
2019	—	`conf`	Toward Understanding the Impact of Staleness in Distributed Machine Learning. ICLR (Poster) Wei Dai, Yi Zhou, Nanqing Dong, Hao Zhang, Eric P. Xing
2019	J	`jnl`	Toward Unsupervised Text Content Manipulation. CoRR Wentao Wang, Zhiting Hu, Zichao Yang, Haoran Shi, Frank F. Xu, Eric P. Xing
2019	J	`jnl`	Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly. CoRR Kirthevasan Kandasamy, Karun Raju Vysyaraju, Willie Neiswanger, Biswajit Paria, Christopher R. Collins, Jeff Schneider, Barnabás Póczos, Eric P. Xing
2019	A*	`conf`	What if We Simply Swap the Two Text Fragments? A Straightforward yet Effective Way to Test the Robustness of Methods to Confounding Signals in Nature Language Inference Tasks. AAAI Haohan Wang, Da Sun, Eric P. Xing
2018	—	`conf`	A Neural Architecture for Automated ICD Coding. ACL (1) Pengtao Xie, Haoran Shi, Ming Zhang, Eric P. Xing
2018	J	`jnl`	AutoLoss: Learning Discrete Schedules for Alternate Optimization. CoRR Haowen Xu, Hao Zhang, Zhiting Hu, Xiaodan Liang, Ruslan Salakhutdinov, Eric P. Xing
2018	—	`conf`	CIRL: Controllable Imitative Reinforcement Learning for Vision-Based Self-driving. ECCV (7) Xiaodan Liang, Tairui Wang, Luona Yang, Eric P. Xing
2018	J	`jnl`	CIRL: Controllable Imitative Reinforcement Learning for Vision-based Self-driving. CoRR Xiaodan Liang, Tairui Wang, Luona Yang, Eric P. Xing
2018	—	`conf`	Cavs: An Efficient Runtime System for Dynamic Neural Networks. USENIX ATC Shizhen Xu, Hao Zhang, Graham Neubig, Wei Dai, Jin Kyu Kim, Zhijie Deng, Qirong Ho, Guangwen Yang, Eric P. Xing
2018	—	`conf`	Classification of Breast Cancer Histopathological Images using Convolutional Neural Networks with Hierarchical Loss and Global Pooling. ICIAR Zeya Wang, Nanqing Dong, Wei Dai, Sean D. Rosario, Eric P. Xing
2018	J	`jnl`	ConnNet: A Long-Range Relation-Aware Pixel-Connectivity Network for Salient Segmentation. CoRR Michael Kampffmeyer, Nanqing Dong, Xiaodan Liang, Yujia Zhang, Eric P. Xing
2018	J	`jnl`	Connecting the Dots Between MLE and RL for Sequence Generation. CoRR Bowen Tan, Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, Eric P. Xing
2018	A*	`conf`	DAGs with NO TEARS: Continuous Optimization for Structure Learning. NeurIPS Xun Zheng, Bryon Aragam, Pradeep Ravikumar, Eric P. Xing
2018	J	`jnl`	DAGs with NO TEARS: Smooth Optimization for Structure Learning. CoRR Xun Zheng, Bryon Aragam, Pradeep Ravikumar, Eric P. Xing
2018	J	`jnl`	DTR-GAN: Dilated Temporal Relational Adversarial Network for Video Summarization. CoRR Yujia Zhang, Michael Kampffmeyer, Xiaodan Liang, Dingwen Zhang, Min Tan, Eric P. Xing
2018	A*	`conf`	Deep Generative Models with Learnable Knowledge Constraints. NeurIPS Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, Lianhui Qin, Xiaodan Liang, Haoye Dong, Eric P. Xing
2018	J	`jnl`	Deep Generative Models with Learnable Knowledge Constraints. CoRR Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, Xiaodan Liang, Lianhui Qin, Haoye Dong, Eric P. Xing
2018	B	`conf`	Deep Learning Based Supervised Semantic Segmentation of Electron Cryo-Subtomograms. ICIP Chang Liu, Xiangrui Zeng, Ruogu Lin, Xiaodan Liang, Zachary Freyberg, Eric P. Xing, Min Xu
2018	J	`jnl`	Deep learning based supervised semantic segmentation of Electron Cryo-Subtomograms. CoRR Chang Liu, Xiangrui Zeng, Ruogu Lin, Xiaodan Liang, Zachary Freyberg, Eric P. Xing, Min Xu
2018	A*	`conf`	DiCE: The Infinitely Differentiable Monte Carlo Estimator. ICML Jakob N. Foerster, Gregory Farquhar, Maruan Al-Shedivat, Tim Rocktäschel, Eric P. Xing, Shimon Whiteson
2018	—	`conf`	DiCE: The Infinitely Differentiable Monte-Carlo Estimator. ICLR (Workshop) Jakob N. Foerster, Gregory Farquhar, Maruan Al-Shedivat, Tim Rocktäschel, Eric P. Xing, Shimon Whiteson
2018	J	`jnl`	DiCE: The Infinitely Differentiable Monte-Carlo Estimator. CoRR Jakob N. Foerster, Gregory Farquhar, Maruan Al-Shedivat, Tim Rocktäschel, Eric P. Xing, Shimon Whiteson
2018	J	`jnl`	Discourse in Multimedia: A Case Study in Information Extraction. CoRR Mrinmaya Sachan, Kumar Avinava Dubey, Eduard H. Hovy, Tom M. Mitchell, Dan Roth, Eric P. Xing
2018	J	`jnl`	Distributed Proximal Gradient Algorithm for Partially Asynchronous Computer Clusters. J. Mach. Learn. Res. Yi Zhou, Yingbin Liang, Yaoliang Yu, Wei Dai, Eric P. Xing
2018	—	`conf`	Domain Adaption in One-Shot Learning. ECML/PKDD (1) Nanqing Dong, Eric P. Xing
2018	A*	`conf`	Dynamic-Structured Semantic Propagation Network. CVPR Xiaodan Liang, Hongfei Zhou, Eric P. Xing
2018	J	`jnl`	Dynamic-structured Semantic Propagation Network. CoRR Xiaodan Liang, Hongfei Zhou, Eric P. Xing
2018	—	`conf`	Effective Use of Bidirectional Language Modeling for Transfer Learning in Biomedical Named Entity Recognition. MLHC Devendra Singh Sachan, Pengtao Xie, Mrinmaya Sachan, Eric P. Xing
2018	J	`jnl`	Ensembles of Lasso Screening Rules. IEEE Trans. Pattern Anal. Mach. Intell. Seunghak Lee, Nico Görnitz, Eric P. Xing, David Heckerman, Christoph Lippert
2018	J	`jnl`	Fair Deep Learning Prediction for Healthcare Applications with Confounder Filtering. CoRR Zhenglin Wu, Haohan Wang, Mingze Cao, Yin Chen, Eric P. Xing
2018	J	`jnl`	Fault Tolerance in Iterative-Convergent Machine Learning. CoRR Aurick Qiao, Bryon Aragam, Bingjing Zhang, Eric P. Xing
2018	A	`conf`	Few-Shot Semantic Segmentation with Prototype Learning. BMVC Nanqing Dong, Eric P. Xing
2018	A*	`conf`	Gated Path Planning Networks. ICML Lisa Lee, Emilio Parisotto, Devendra Singh Chaplot, Eric P. Xing, Ruslan Salakhutdinov
2018	J	`jnl`	Gated Path Planning Networks. CoRR Lisa Lee, Emilio Parisotto, Devendra Singh Chaplot, Eric P. Xing, Ruslan Salakhutdinov
2018	—	`conf`	Generative Semantic Manipulation with Mask-Contrasting GAN. ECCV (13) Xiaodan Liang, Hao Zhang, Liang Lin, Eric P. Xing
2018	J	`jnl`	Geometric Generalization Based Zero-Shot Learning Dataset Infinite World: Simple Yet Powerful. CoRR Rajesh Chidambaram, Michael Kampffmeyer, Willie Neiswanger, Xiaodan Liang, Thomas Lachmann, Eric P. Xing
2018	A*	`conf`	Hybrid Retrieval-Generation Reinforced Agent for Medical Image Report Generation. NeurIPS Yuan Li, Xiaodan Liang, Zhiting Hu, Eric P. Xing
2018	J	`jnl`	Hybrid Retrieval-Generation Reinforced Agent for Medical Image Report Generation. CoRR Christy Y. Li, Xiaodan Liang, Zhiting Hu, Eric P. Xing
2018	J	`jnl`	Hybrid Subspace Learning for High-Dimensional Data. CoRR Micol Marchetti-Bowick, Benjamin J. Lengerich, Ankur P. Parikh, Eric P. Xing
2018	J	`jnl`	Identifiability of Nonparametric Mixture Models and Bayes Optimal Clustering. CoRR Bryon Aragam, Chen Dan, Pradeep Ravikumar, Eric P. Xing
2018	A	`conf`	Image-derived generative modeling of pseudo-macromolecular structures - towards the statistical assessment of Electron CryoTomography template matching. BMVC Kaiwen Wang, Xiangrui Zeng, Xiaodan Liang, Zhiguang Huo, Eric P. Xing, Min Xu
2018	J	`jnl`	Image-derived generative modeling of pseudo-macromolecular structures - towards the statistical assessment of Electron CryoTomography template matching. CoRR Kaiwen Wang, Xiangrui Zeng, Xiaodan Liang, Zhiguang Huo, Eric P. Xing, Min Xu
2018	A*	`conf`	Learning Pipelines with Limited Data and Domain Knowledge: A Study in Parsing Physics Problems. NeurIPS Mrinmaya Sachan, Kumar Avinava Dubey, Tom M. Mitchell, Dan Roth, Eric P. Xing
2018	—	`conf`	Litz: Elastic Framework for High-Performance Distributed Machine Learning. USENIX ATC Aurick Qiao, Abutalib Aghayev, Weiren Yu, Haoyang Chen, Qirong Ho, Garth A. Gibson, Eric P. Xing
2018	J	`jnl`	Missing Value Imputation Based on Deep Generative Models. CoRR Hongbao Zhang, Pengtao Xie, Eric P. Xing
2018	J	`jnl`	Multimodal Machine Learning for Automated ICD Coding. CoRR Keyang Xu, Mike Lam, Jingzhi Pang, Xin Gao, Charlotte Band, Piyush Mathur, Frank Papay, Ashish K. Khanna, Jacek B. Cywinski, Kamal Maheshwari, Pengtao Xie, Eric P. Xing
2018	A*	`conf`	Neural Architecture Search with Bayesian Optimisation and Optimal Transport. NeurIPS Kirthevasan Kandasamy, Willie Neiswanger, Jeff Schneider, Barnabás Póczos, Eric P. Xing
2018	J	`jnl`	Neural Architecture Search with Bayesian Optimisation and Optimal Transport. CoRR Kirthevasan Kandasamy, Willie Neiswanger, Jeff Schneider, Barnabás Póczos, Eric P. Xing
2018	A*	`conf`	Nonoverlap-Promoting Variable Selection. ICML Pengtao Xie, Hongbao Zhang, Yichen Zhu, Eric P. Xing
2018	—	`conf`	On Unifying Deep Generative Models. ICLR (Poster) Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, Eric P. Xing
2018	—	`conf`	On the Automatic Generation of Medical Imaging Reports. ACL (1) Baoyu Jing, Pengtao Xie, Eric P. Xing
2018	J	`jnl`	On the Complexity of Exploration in Goal-Driven Navigation. CoRR Maruan Al-Shedivat, Lisa Lee, Ruslan Salakhutdinov, Eric P. Xing
2018	—	`conf`	Orpheus: Efficient Distributed Machine Learning via System and Algorithm Co-design. SoCC Pengtao Xie, Jin Kyu Kim, Qirong Ho, Yaoliang Yu, Eric P. Xing
2018	A*	`conf`	Orthogonality-Promoting Distance Metric Learning: Convex Relaxation and Theoretical Analysis. ICML Pengtao Xie, Wei Wu, Yichen Zhu, Eric P. Xing
2018	J	`jnl`	Orthogonality-Promoting Distance Metric Learning: Convex Relaxation and Theoretical Analysis. CoRR Pengtao Xie, Wei Wu, Yichen Zhu, Eric P. Xing
2018	A*	`conf`	Parsing to Programs: A Framework for Situated QA. KDD Mrinmaya Sachan, Eric P. Xing
2018	J	`jnl`	Personalized Survival Prediction with Contextual Explanation Networks. CoRR Maruan Al-Shedivat, Avinava Dubey, Eric P. Xing
2018	J	`jnl`	Personalized regression enables sample-specific pan-cancer analysis. Bioinform. Benjamin J. Lengerich, Bryon Aragam, Eric P. Xing
2018	A	`conf`	Query-Conditioned Three-Player Adversarial Network for Video Summarization. BMVC Yujia Zhang, Michael Kampffmeyer, Xiaodan Liang, Min Tan, Eric P. Xing
2018	J	`jnl`	Query-Conditioned Three-Player Adversarial Network for Video Summarization. CoRR Yujia Zhang, Michael Kampffmeyer, Xiaodan Liang, Min Tan, Eric P. Xing
2018	—	`conf`	Real-to-Virtual Domain Unification for End-to-End Autonomous Driving. ECCV (4) Luona Yang, Xiaodan Liang, Tairui Wang, Eric P. Xing
2018	—	`conf`	Reinforced Auto-Zoom Net: Towards Accurate and Fast Breast Cancer Segmentation in Whole-Slide Images. DLMIA/ML-CDS@MICCAI Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang, Zeya Wang, Wei Dai, Eric P. Xing
2018	J	`jnl`	Reinforced Auto-Zoom Net: Towards Accurate and Fast Breast Cancer Segmentation in Whole-slide Images. CoRR Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang, Zeya Wang, Wei Dai, Eric P. Xing
2018	J	`jnl`	Rethinking Knowledge Graph Propagation for Zero-Shot Learning. CoRR Michael Kampffmeyer, Yinbo Chen, Xiaodan Liang, Hao Wang, Yujia Zhang, Eric P. Xing
2018	—	`conf`	SCAN: Structure Correcting Adversarial Network for Organ Segmentation in Chest X-Rays. DLMIA/ML-CDS@MICCAI Wei Dai, Nanqing Dong, Zeya Wang, Xiaodan Liang, Hao Zhang, Eric P. Xing
2018	J	`jnl`	Sample Complexity of Nonparametric Semi-Supervised Learning. CoRR Chen Dan, Liu Leqi, Bryon Aragam, Pradeep Ravikumar, Eric P. Xing
2018	—	`conf`	Self-Training for Jointly Learning to Ask and Answer Questions. NAACL-HLT Mrinmaya Sachan, Eric P. Xing
2018	A	`conf`	Semantic-aware Grad-GAN for Virtual-to-Real Urban Scene Adaption. BMVC Peilun Li, Xiaodan Liang, Daoyuan Jia, Eric P. Xing
2018	J	`jnl`	Semantic-aware Grad-GAN for Virtual-to-Real Urban Scene Adaption. CoRR Peilun Li, Xiaodan Liang, Daoyuan Jia, Eric P. Xing
2018	J	`jnl`	Stackelberg GAN: Towards Provable Minimax Equilibrium via Multi-Generator Architectures. CoRR Hongyang Zhang, Susu Xu, Jiantao Jiao, Pengtao Xie, Ruslan Salakhutdinov, Eric P. Xing
2018	A*	`conf`	Symbolic Graph Reasoning Meets Convolutions. NeurIPS Xiaodan Liang, Zhiting Hu, Hao Zhang, Liang Lin, Eric P. Xing
2018	A*	`conf`	SysML: On System and Algorithm Co-design for Practical Machine Learning. KDD Eric P. Xing
2018	J	`jnl`	Texar: A Modularized, Versatile, and Extensible Toolkit for Text Generation. CoRR Zhiting Hu, Haoran Shi, Zichao Yang, Bowen Tan, Tiancheng Zhao, Junxian He, Wentao Wang, Xingjiang Yu, Lianhui Qin, Di Wang, Xuezhe Ma, Zhengzhong Liu, Xiaodan Liang, Wanrong Zhu, Devendra Singh Sachan, Eric P. Xing
2018	J	`jnl`	The Intriguing Properties of Model Explanations. CoRR Maruan Al-Shedivat, Avinava Dubey, Eric P. Xing
2018	A*	`conf`	The Sample Complexity of Semi-Supervised Learning with Nonparametric Mixture Models. NeurIPS Chen Dan, Liu Leqi, Bryon Aragam, Pradeep Ravikumar, Eric P. Xing
2018	J	`jnl`	Toward Understanding the Impact of Staleness in Distributed Machine Learning. CoRR Wei Dai, Yi Zhou, Nanqing Dong, Hao Zhang, Eric P. Xing
2018	A*	`conf`	Transformation Autoregressive Networks. ICML Junier B. Oliva, Avinava Dubey, Manzil Zaheer, Barnabás Póczos, Ruslan Salakhutdinov, Eric P. Xing, Jeff Schneider
2018	—	`conf`	Unsupervised Domain Adaptation for Automatic Estimation of Cardiothoracic Ratio. MICCAI (2) Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang, Zeya Wang, Wei Dai, Eric P. Xing
2018	J	`jnl`	Unsupervised Domain Adaptation for Automatic Estimation of Cardiothoracic Ratio. CoRR Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang, Zeya Wang, Wei Dai, Eric P. Xing
2018	J	`jnl`	Unsupervised Object-Level Video Summarization with Online Motion Auto-Encoder. CoRR Yujia Zhang, Xiaodan Liang, Dingwen Zhang, Min Tan, Eric P. Xing
2018	J	`jnl`	Unsupervised Pseudo-Labeling for Extractive Summarization on Electronic Health Records. CoRR Xiangan Liu, Keyang Xu, Pengtao Xie, Eric P. Xing
2018	J	`jnl`	Unsupervised Real-to-Virtual Domain Unification for End-to-End Highway Driving. CoRR Luona Yang, Xiaodan Liang, Eric P. Xing
2018	A*	`conf`	Unsupervised Text Style Transfer using Language Models as Discriminators. NeurIPS Zichao Yang, Zhiting Hu, Chris Dyer, Eric P. Xing, Taylor Berg-Kirkpatrick
2018	J	`jnl`	Unsupervised Text Style Transfer using Language Models as Discriminators. CoRR Zichao Yang, Zhiting Hu, Chris Dyer, Eric P. Xing, Taylor Berg-Kirkpatrick
2018	J	`jnl`	What If We Simply Swap the Two Text Fragments? A Straightforward yet Effective Way to Test the Robustness of Methods to Confounding Signals in Nature Language Inference Tasks. CoRR Haohan Wang, Da Sun, Eric P. Xing
2017	—	`conf`	A Constituent-Centric Neural Architecture for Reading Comprehension. ACL (1) Pengtao Xie, Eric P. Xing
2017	J	`jnl`	A Sparse Graph-Structured Lasso Mixed Model for Genetic Association with Confounding Correction. CoRR Wenting Ye, Xiang Liu, Haohan Wang, Eric P. Xing
2017	—	`conf`	Adversarial Connective-exploiting Networks for Implicit Discourse Relation Classification. ACL (1) Lianhui Qin, Zhisong Zhang, Hai Zhao, Zhiting Hu, Eric P. Xing
2017	J	`jnl`	Adversarial Connective-exploiting Networks for Implicit Discourse Relation Classification. CoRR Lianhui Qin, Zhisong Zhang, Hai Zhao, Zhiting Hu, Eric P. Xing
2017	J	`jnl`	Cavs: A Vertex-centric Programming Interface for Dynamic Neural Networks. CoRR Hao Zhang, Shizhen Xu, Graham Neubig, Wei Dai, Qirong Ho, Guangwen Yang, Eric P. Xing
2017	J	`jnl`	Contextual Explanation Networks. CoRR Maruan Al-Shedivat, Avinava Dubey, Eric P. Xing
2017	J	`jnl`	Controllable Text Generation. CoRR Zhiting Hu, Zichao Yang, Xiaodan Liang, Ruslan Salakhutdinov, Eric P. Xing
2017	J	`jnl`	Convolutional Neural Networks for Medical Diagnosis from Admission Notes. CoRR Christy Y. Li, Dimitris Konomis, Graham Neubig, Pengtao Xie, Carol Cheng, Eric P. Xing
2017	A*	`conf`	Deep Determinantal Point Process for Large-Scale Multi-label Classification. ICCV Pengtao Xie, Ruslan Salakhutdinov, Luntian Mou, Eric P. Xing
2017	A*	`conf`	Deep Variation-Structured Reinforcement Learning for Visual Relationship and Attribute Detection. CVPR Xiaodan Liang, Lisa Lee, Eric P. Xing
2017	J	`jnl`	Deep Variation-structured Reinforcement Learning for Visual Relationship and Attribute Detection. CoRR Xiaodan Liang, Lisa Lee, Eric P. Xing
2017	J	`jnl`	Deep learning-based subdivision approach for large scale macromolecules structure recovery from electron cryo tomograms. Bioinform. Min Xu, Xiaoqi Chai, Hariank Muthakana, Xiaodan Liang, Ge Yang, Tzviya Zeev-Ben-Mordehai, Eric P. Xing
2017	J	`jnl`	Diversity-Promoting Bayesian Learning of Latent Variable Models. CoRR Pengtao Xie, Jun Zhu, Eric P. Xing
2017	A*	`conf`	Dual Motion GAN for Future-Flow Embedded Video Prediction. ICCV Xiaodan Liang, Lisa Lee, Wei Dai, Eric P. Xing
2017	J	`jnl`	Dual Motion GAN for Future-Flow Embedded Video Prediction. CoRR Xiaodan Liang, Lisa Lee, Wei Dai, Eric P. Xing
2017	J	`jnl`	Effective Use of Bidirectional Language Modeling for Medical Named Entity Recognition. CoRR Devendra Singh Sachan, Pengtao Xie, Eric P. Xing
2017	A*	`conf`	Efficient Correlated Topic Modeling with Topic Embedding. KDD Junxian He, Zhiting Hu, Taylor Berg-Kirkpatrick, Ying Huang, Eric P. Xing
2017	J	`jnl`	Efficient Correlated Topic Modeling with Topic Embedding. CoRR Junxian He, Zhiting Hu, Taylor Berg-Kirkpatrick, Ying Huang, Eric P. Xing
2017	A*	`conf`	Efficient Multiple Instance Metric Learning Using Weakly Supervised Data. CVPR Marc T. Law, Yaoliang Yu, Raquel Urtasun, Richard S. Zemel, Eric P. Xing
2017	A*	`conf`	From Textbooks to Knowledge: A Case Study in Harvesting Axiomatic Knowledge from Textbooks to Solve Geometry Problems. EMNLP Mrinmaya Sachan, Avinava Dubey, Eric P. Xing
2017	J	`jnl`	Generative Semantic Manipulation with Contrasting GAN. CoRR Xiaodan Liang, Hao Zhang, Eric P. Xing
2017	A*	`conf`	Interpretable Structure-Evolving LSTM. CVPR Xiaodan Liang, Liang Lin, Xiaohui Shen, Jiashi Feng, Shuicheng Yan, Eric P. Xing
2017	J	`jnl`	Interpretable Structure-Evolving LSTM. CoRR Xiaodan Liang, Liang Lin, Xiaohui Shen, Jiashi Feng, Shuicheng Yan, Eric P. Xing
2017	A*	`conf`	Learning Latent Space Models with Angular Constraints. ICML Pengtao Xie, Yuntian Deng, Yi Zhou, Abhimanu Kumar, Yaoliang Yu, James Zou, Eric P. Xing
2017	J	`jnl`	Learning Less-Overlapping Representations. CoRR Pengtao Xie, Hongbao Zhang, Eric P. Xing
2017	J	`jnl`	Learning Scalable Deep Kernels with Recurrent Structure. J. Mach. Learn. Res. Maruan Al-Shedivat, Andrew Gordon Wilson, Yunus Saatchi, Zhiting Hu, Eric P. Xing
2017	—	`conf`	Learning to Solve Geometry Problems from Natural Language Demonstrations in Textbooks. *SEM Mrinmaya Sachan, Eric P. Xing
2017	J	`jnl`	Medical Diagnosis From Laboratory Tests by Combining Generative and Discriminative Learning. CoRR Shiyue Zhang, Pengtao Xie, Dong Wang, Eric P. Xing
2017	—	`conf`	Multiplex confounding factor correction for genomic association mapping with squared sparse linear mixed model. BIBM Haohan Wang, Xiang Liu, Yunpeng Xiao, Ming Xu, Eric P. Xing
2017	A	`conf`	Near-Orthogonality Regularization in Kernel Methods. UAI Pengtao Xie, Barnabás Póczos, Eric P. Xing
2017	A*	`conf`	Nonparametric Variational Auto-Encoders for Hierarchical Representation Learning. ICCV Prasoon Goyal, Zhiting Hu, Xiaodan Liang, Chenyu Wang, Eric P. Xing, Carnegie Mellon
2017	J	`jnl`	Nonparametric Variational Auto-encoders for Hierarchical Representation Learning. CoRR Prasoon Goyal, Zhiting Hu, Xiaodan Liang, Chenyu Wang, Eric P. Xing
2017	J	`jnl`	On Unifying Deep Generative Models. CoRR Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, Eric P. Xing
2017	J	`jnl`	On the Automatic Generation of Medical Imaging Reports. CoRR Baoyu Jing, Pengtao Xie, Eric P. Xing
2017	J	`jnl`	On the Origin of Deep Learning. CoRR Haohan Wang, Bhiksha Raj, Eric P. Xing
2017	A*	`conf`	PPDsparse: A Parallel Primal-Dual Sparse Method for Extreme Classification. KDD Ian En-Hsu Yen, Xiangru Huang, Wei Dai, Pradeep Ravikumar, Inderjit S. Dhillon, Eric P. Xing
2017	—	`conf`	Poseidon: An Efficient Communication Architecture for Distributed Deep Learning on GPU Clusters. USENIX ATC Hao Zhang, Zeyu Zheng, Shizhen Xu, Wei Dai, Qirong Ho, Xiaodan Liang, Zhiting Hu, Jinliang Wei, Pengtao Xie, Eric P. Xing
2017	J	`jnl`	Poseidon: An Efficient Communication Architecture for Distributed Deep Learning on GPU Clusters. CoRR Hao Zhang, Zeyu Zheng, Shizhen Xu, Wei Dai, Qirong Ho, Xiaodan Liang, Zhiting Hu, Jinliang Wei, Pengtao Xie, Eric P. Xing
2017	A*	`conf`	Post-Inference Prior Swapping. ICML Willie Neiswanger, Eric P. Xing
2017	J	`jnl`	Predicting Discharge Medications at Admission Time Based on Deep Learning. CoRR Yuan Yang, Pengtao Xie, Xin Gao, Carol Cheng, Christy Y. Li, Hongbao Zhang, Eric P. Xing
2017	A*	`conf`	Randomization or Condensation?: Linear-Cost Matrix Sketching Via Cascaded Compression Sampling. KDD Kai Zhang, Chuanren Liu, Jie Zhang, Hui Xiong, Eric P. Xing, Jieping Ye
2017	J	`jnl`	Recurrent Estimation of Distributions. CoRR Junier B. Oliva, Kumar Avinava Dubey, Barnabás Póczos, Eric P. Xing, Jeff G. Schneider
2017	A*	`conf`	Recurrent Topic-Transition GAN for Visual Paragraph Generation. ICCV Xiaodan Liang, Zhiting Hu, Hao Zhang, Chuang Gan, Eric P. Xing
2017	J	`jnl`	Recurrent Topic-Transition GAN for Visual Paragraph Generation. CoRR Xiaodan Liang, Zhiting Hu, Hao Zhang, Chuang Gan, Eric P. Xing
2017	J	`jnl`	SCAN: Structure Correcting Adversarial Network for Chest X-rays Organ Segmentation. CoRR Wei Dai, Joseph Doyle, Xiaodan Liang, Hao Zhang, Nanqing Dong, Yuan Li, Eric P. Xing
2017	A	`conf`	Select-additive learning: Improving generalization in multimodal sentiment analysis. ICME Haohan Wang, Aaksha Meghawat, Louis-Philippe Morency, Eric P. Xing
2017	J	`jnl`	Semantic Pooling for Complex Event Analysis in Untrimmed Videos. IEEE Trans. Pattern Anal. Mach. Intell. Xiaojun Chang, Yaoliang Yu, Yi Yang, Eric P. Xing
2017	J	`jnl`	Stability Selection for Structured Variable Selection. CoRR George Philipp, Seunghak Lee, Eric P. Xing
2017	J	`jnl`	State Space LSTM Models with Particle MCMC Inference. CoRR Xun Zheng, Manzil Zaheer, Amr Ahmed, Yuan Wang, Eric P. Xing, Alexander J. Smola
2017	—	`conf`	Structured Generative Adversarial Networks. NIPS Zhijie Deng, Hao Zhang, Xiaodan Liang, Luona Yang, Shizhen Xu, Jun Zhu, Eric P. Xing
2017	J	`jnl`	Structured Generative Adversarial Networks. CoRR Zhijie Deng, Hao Zhang, Xiaodan Liang, Luona Yang, Shizhen Xu, Jun Zhu, Eric P. Xing
2017	J	`jnl`	Techniques for proving Asynchronous Convergence results for Markov Chain Monte Carlo methods. CoRR Alexander Terenin, Eric P. Xing
2017	A*	`conf`	Toward Controlled Generation of Text. ICML Zhiting Hu, Zichao Yang, Xiaodan Liang, Ruslan Salakhutdinov, Eric P. Xing
2017	J	`jnl`	Towards Automated ICD Coding Using Deep Learning. CoRR Haoran Shi, Pengtao Xie, Zhiting Hu, Ming Zhang, Eric P. Xing
2017	A*	`conf`	Uncorrelation and Evenness: a New Diversity-Promoting Regularizer. ICML Pengtao Xie, Aarti Singh, Eric P. Xing
2017	—	`conf`	Variable selection in heterogeneous datasets: A truncated-rank sparse linear mixed model with applications to genome-wide association studies. BIBM Haohan Wang, Bryon Aragam, Eric P. Xing
2017	J	`jnl`	Visual Explanations for Convolutional Neural Networks via Input Resampling. CoRR Benjamin J. Lengerich, Sandeep Konam, Eric P. Xing, Stephanie Rosenthal, Manuela M. Veloso
2017	J	`jnl`	ZM-Net: Real-time Zero-shot Image Manipulation Network. CoRR Hao Wang, Xiaodan Liang, Hao Zhang, Dit-Yan Yeung, Eric P. Xing
2016	J	`jnl`	A network-driven approach for genome-wide association mapping. Bioinform. Seunghak Lee, Soonho Kong, Eric P. Xing
2016	J	`jnl`	A time-varying group sparse additive model for genome-wide association studies of dynamic complex traits. Bioinform. Micol Marchetti-Bowick, Junming Yin, Judie A. Howrylak, Eric P. Xing
2016	—	`conf`	Addressing the straggler problem for iterative convergent parallel ML. SoCC Aaron Harlap, Henggang Cui, Wei Dai, Jinliang Wei, Gregory R. Ganger, Phillip B. Gibbons, Garth A. Gibson, Eric P. Xing
2016	—	`conf`	Advanced Machine Learning for Healthcare. CRI Jimeng Sun, Jim Rehg, Suchi Saria, Hua Xu, Eric P. Xing
2016	J	`jnl`	An Efficient Nonlinear Regression Approach for Genome-wide Detection of Marginal and Interacting Genetic Variations. J. Comput. Biol. Seunghak Lee, Aurélie C. Lozano, Prabhanjan Kambadur, Eric P. Xing
2016	A	`conf`	Bayesian Nonparametric Kernel-Learning. AISTATS Junier B. Oliva, Avinava Dubey, Andrew Gordon Wilson, Barnabás Póczos, Jeff G. Schneider, Eric P. Xing
2016	A*	`conf`	Closed-Form Training of Mahalanobis Distance for Supervised Clustering. CVPR Marc T. Law, Yaoliang Yu, Matthieu Cord, Eric P. Xing
2016	A	`conf`	Deep Kernel Learning. AISTATS Andrew Gordon Wilson, Zhiting Hu, Ruslan Salakhutdinov, Eric P. Xing
2016	A*	`conf`	Deep Neural Networks with Massive Learned Knowledge. EMNLP Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, Eric P. Xing
2016	A*	`conf`	Diversity-Promoting Bayesian Learning of Latent Variable Models. ICML Pengtao Xie, Jun Zhu, Eric P. Xing
2016	—	`conf`	Easy Questions First? A Case Study on Curriculum Learning for Question Answering. ACL (1) Mrinmaya Sachan, Eric P. Xing
2016	A	`conf`	GeePS: scalable deep learning on distributed GPUs with a GPU-specialized parameter server. EuroSys Henggang Cui, Hao Zhang, Gregory R. Ganger, Phillip B. Gibbons, Eric P. Xing
2016	A*	`conf`	Grounding Topic Models with Knowledge Bases. IJCAI Zhiting Hu, Gang Luo, Mrinmaya Sachan, Eric P. Xing, Zaiqing Nie
2016	—	`conf`	Harnessing Deep Neural Networks with Logic Rules. ACL (1) Zhiting Hu, Xuezhe Ma, Zhengzhong Liu, Eduard H. Hovy, Eric P. Xing
2016	J	`jnl`	Harnessing Deep Neural Networks with Logic Rules. CoRR Zhiting Hu, Xuezhe Ma, Zhengzhong Liu, Eduard H. Hovy, Eric P. Xing
2016	J	`jnl`	Latent Space Inference of Internet-Scale Networks. J. Mach. Learn. Res. Qirong Ho, Junming Yin, Eric P. Xing
2016	—	`conf`	Learning Concept Taxonomies from Multi-modal Data. ACL (1) Hao Zhang, Zhiting Hu, Yuntian Deng, Mrinmaya Sachan, Zhicheng Yan, Eric P. Xing
2016	J	`jnl`	Learning Concept Taxonomies from Multi-modal Data. CoRR Hao Zhang, Zhiting Hu, Yuntian Deng, Mrinmaya Sachan, Zhicheng Yan, Eric P. Xing
2016	—	`conf`	Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices. NIPS Kirthevasan Kandasamy, Maruan Al-Shedivat, Eric P. Xing
2016	J	`jnl`	Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices. CoRR Kirthevasan Kandasamy, Maruan Al-Shedivat, Eric P. Xing
2016	J	`jnl`	Learning Scalable Deep Kernels with Recurrent Structure. CoRR Maruan Al-Shedivat, Andrew Gordon Wilson, Yunus Saatchi, Zhiting Hu, Eric P. Xing
2016	A	`conf`	Lighter-Communication Distributed Machine Learning via Sufficient Factor Broadcasting. UAI Pengtao Xie, Jin Kyu Kim, Yi Zhou, Qirong Ho, Abhimanu Kumar, Yaoliang Yu, Eric P. Xing
2016	—	`conf`	Machine Comprehension using Rich Semantic Representations. ACL (2) Mrinmaya Sachan, Eric P. Xing
2016	J	`jnl`	Multimodal Data Mining in a Multimedia Database Based on Structured Max Margin Learning. ACM Trans. Knowl. Discov. Data Zhen Guo, Zhongfei (Mark) Zhang, Eric P. Xing, Christos Faloutsos
2016	J	`jnl`	Nonparametric Decentralized Detection and Sparse Sensor Selection Via Weighted Kernel. IEEE Trans. Signal Process. Weiguang Wang, Yingbin Liang, Eric P. Xing, Lixin Shen
2016	A	`conf`	On Convergence of Model Parallel Proximal Gradient Algorithm for Stale Synchronous Parallel System. AISTATS Yi Zhou, Yaoliang Yu, Wei Dai, Yingbin Liang, Eric P. Xing
2016	A*	`conf`	Parallel and Distributed Block-Coordinate Frank-Wolfe Algorithms. ICML Yu-Xiang Wang, Veeranjaneyulu Sadhanala, Wei Dai, Willie Neiswanger, Suvrit Sra, Eric P. Xing
2016	J	`jnl`	Prior Swapping for Data-Independent Inference. CoRR Willie Neiswanger, Eric P. Xing
2016	A	`conf`	STRADS: a distributed framework for scheduled model parallel machine learning. EuroSys Jin Kyu Kim, Qirong Ho, Seunghak Lee, Xun Zheng, Wei Dai, Garth A. Gibson, Eric P. Xing
2016	A	`conf`	Scalable Gaussian Processes for Characterizing Multidimensional Change Surfaces. AISTATS William Herlands, Andrew Gordon Wilson, Hannes Nickisch, Seth R. Flaxman, Daniel B. Neill, Wilbert Van Panhuis, Eric P. Xing
2016	A*	`conf`	Scalable Time-Decaying Adaptive Prediction Algorithm. KDD Yinyan Tan, Zhe Fan, Guilin Li, Fangshan Wang, Zhengbing Li, Shikai Liu, Qiuling Pan, Eric P. Xing, Qirong Ho
2016	A	`conf`	Scalable and Sound Low-Rank Tensor Learning. AISTATS Hao Cheng, Yaoliang Yu, Xinhua Zhang, Eric P. Xing, Dale Schuurmans
2016	—	`conf`	Science Question Answering using Instructional Materials. ACL (2) Mrinmaya Sachan, Kumar Avinava Dubey, Eric P. Xing
2016	J	`jnl`	Science Question Answering using Instructional Materials. CoRR Mrinmaya Sachan, Avinava Dubey, Eric P. Xing
2016	J	`jnl`	SeDMiD for Confusion Detection: Uncovering Mind State from Time Series Brain Wave Data. CoRR Jingkang Yang, Haohan Wang, Jun Zhu, Eric P. Xing
2016	J	`jnl`	Seeing the Forest from the Trees in Two Looks: Matrix Sketching by Cascaded Bilateral Sampling. CoRR Kai Zhang, Chuanren Liu, Jie Zhang, Hui Xiong, Eric P. Xing, Jieping Ye
2016	J	`jnl`	Select-Additive Learning: Improving Cross-individual Generalization in Multimodal Sentiment Analysis. CoRR Haohan Wang, Aaksha Meghawat, Louis-Philippe Morency, Eric P. Xing
2016	J	`jnl`	Sparse Output Coding for Scalable Visual Recognition. Int. J. Comput. Vis. Bin Zhao, Eric P. Xing
2016	—	`conf`	Stochastic Variational Deep Kernel Learning. NIPS Andrew Gordon Wilson, Zhiting Hu, Ruslan Salakhutdinov, Eric P. Xing
2016	J	`jnl`	Stochastic Variational Deep Kernel Learning. CoRR Andrew Gordon Wilson, Zhiting Hu, Ruslan Salakhutdinov, Eric P. Xing
2016	A*	`conf`	They are Not Equally Reliable: Semantic Event Search Using Differentiated Concept Classifiers. CVPR Xiaojun Chang, Yaoliang Yu, Yi Yang, Eric P. Xing
2016	—	`conf`	Variance Reduction in Stochastic Gradient Langevin Dynamics. NIPS Kumar Avinava Dubey, Sashank J. Reddi, Sinead A. Williamson, Barnabás Póczos, Alexander J. Smola, Eric P. Xing
2015	J	`jnl`	AD J. Mach. Learn. Res. André F. T. Martins, Mário A. T. Figueiredo, Pedro M. Q. Aguiar, Noah A. Smith, Eric P. Xing
2015	A*	`conf`	An Active Learning Approach to Coreference Resolution. IJCAI Mrinmaya Sachan, Eduard H. Hovy, Eric P. Xing
2015	B	`conf`	An Efficient Nonlinear Regression Approach for Genome-Wide Detection of Marginal and Interacting Genetic Variations. RECOMB Seunghak Lee, Aurélie C. Lozano, Prabhanjan Kambadur, Eric P. Xing
2015	A	`conf`	Big Data: New Paradigm or "Sound and Fury, Signifying Nothing"? WSDM Andrei Z. Broder, Lada A. Adamic, Michael J. Franklin, Maarten de Rijke, Eric P. Xing, Kai Yu
2015	J	`jnl`	Collective Support Recovery for Multi-Design Multi-Response Linear Regression. IEEE Trans. Inf. Theory Weiguang Wang, Yingbin Liang, Eric P. Xing
2015	—	`conf`	Community Level Diffusion Extraction. SIGMOD Conference Zhiting Hu, Junjie Yao, Bin Cui, Eric P. Xing
2015	A*	`conf`	Complex Event Detection using Semantic Saliency and Nearly-Isotonic SVM. ICML Xiaojun Chang, Yi Yang, Eric P. Xing, Yaoliang Yu
2015	J	`jnl`	Deep Kernel Learning. CoRR Andrew Gordon Wilson, Zhiting Hu, Ruslan Salakhutdinov, Eric P. Xing
2015	J	`jnl`	Distributed Machine Learning via Sufficient Factor Broadcasting. CoRR Pengtao Xie, Jin Kyu Kim, Yi Zhou, Qirong Ho, Abhimanu Kumar, Yaoliang Yu, Eric P. Xing
2015	A*	`conf`	Diversifying Restricted Boltzmann Machine for Document Modeling. KDD Pengtao Xie, Yuntian Deng, Eric P. Xing
2015	A*	`conf`	Dynamic Topic Modeling for Monitoring Market Competition from Online Text and Image Data. KDD Hao Zhang, Gunhee Kim, Eric P. Xing
2015	J	`jnl`	Embarrassingly Parallel Variational Inference in Nonconjugate Models. CoRR Willie Neiswanger, Chong Wang, Eric P. Xing
2015	—	`conf`	Entity Hierarchy Embedding. ACL (1) Zhiting Hu, Poyao Huang, Yuntian Deng, Yingkai Gao, Eric P. Xing
2015	A	`conf`	Fast Function to Function Regression. AISTATS Junier B. Oliva, Willie Neiswanger, Barnabás Póczos, Eric P. Xing, Hy Trac, Shirley Ho, Jeff G. Schneider
2015	A*	`conf`	High-Performance Distributed ML at Scale through Parameter Server Consistency Models. AAAI Wei Dai, Abhimanu Kumar, Jinliang Wei, Qirong Ho, Garth A. Gibson, Eric P. Xing
2015	—	`conf`	Incorporating Word Correlation Knowledge into Topic Modeling. HLT-NAACL Pengtao Xie, Diyi Yang, Eric P. Xing
2015	A*	`conf`	Integrating Image Clustering and Codebook Learning. AAAI Pengtao Xie, Eric P. Xing
2015	J	`jnl`	Kernel methods for large-scale genomic data analysis. Briefings Bioinform. Xuefeng Wang, Eric P. Xing, Daniel J. Schaid
2015	A*	`conf`	Large-scale Distributed Dependent Nonparametric Trees. ICML Zhiting Hu, Qirong Ho, Avinava Dubey, Eric P. Xing
2015	J	`jnl`	Latent Variable Modeling with Diversity-Inducing Mutual Angular Regularization. CoRR Pengtao Xie, Yuntian Deng, Eric P. Xing
2015	—	`conf`	Learning Answer-Entailing Structures for Machine Comprehension. ACL (1) Mrinmaya Sachan, Kumar Avinava Dubey, Eric P. Xing, Matthew Richardson
2015	A*	`conf`	Linear Time Samplers for Supervised Topic Models using Compositional Proposals. KDD Xun Zheng, Yaoliang Yu, Eric P. Xing
2015	—	`conf`	Managed communication and consistency for fast data-parallel iterative analytics. SoCC Jinliang Wei, Wei Dai, Aurick Qiao, Qirong Ho, Henggang Cui, Gregory R. Ganger, Phillip B. Gibbons, Garth A. Gibson, Eric P. Xing
2015	A	`conf`	Minimizing Nonconvex Non-Separable Functions. AISTATS Yaoliang Yu, Xun Zheng, Micol Marchetti-Bowick, Eric P. Xing
2015	A*	`conf`	Mining User Interests from Personal Photos. AAAI Pengtao Xie, Yulong Pei, Yuan Xie, Eric P. Xing
2015	J	`jnl`	On the Generalization Error Bounds of Neural Networks under Diversity-Inducing Mutual Angular Regularization. CoRR Pengtao Xie, Yuntian Deng, Eric P. Xing
2015	A*	`conf`	Petuum: A New Platform for Distributed Machine Learning on Big Data. KDD Eric P. Xing, Qirong Ho, Wei Dai, Jin Kyu Kim, Jinliang Wei, Seunghak Lee, Xun Zheng, Pengtao Xie, Abhimanu Kumar, Yaoliang Yu
2015	J	`jnl`	Petuum: A New Platform for Distributed Machine Learning on Big Data. IEEE Trans. Big Data Eric P. Xing, Qirong Ho, Wei Dai, Jin Kyu Kim, Jinliang Wei, Seunghak Lee, Xun Zheng, Pengtao Xie, Abhimanu Kumar, Yaoliang Yu
2015	J	`jnl`	Poseidon: A System Architecture for Efficient GPU-based Deep Learning on Multiple Machines. CoRR Hao Zhang, Zhiting Hu, Jinliang Wei, Pengtao Xie, Gunhee Kim, Qirong Ho, Eric P. Xing
2015	J	`jnl`	Scalable Modeling of Conversational-role based Self-presentation Characteristics in Large Online Forums. CoRR Abhimanu Kumar, Shriphani Palakodety, Chong Wang, Carolyn P. Rosé, Eric P. Xing, Miaomiao Wen
2015	A*	`conf`	Semantic Concept Discovery for Large-Scale Zero-Shot Event Detection. IJCAI Xiaojun Chang, Yi Yang, Alexander G. Hauptmann, Eric P. Xing, Yaoliang Yu
2015	J	`jnl`	Strategies and Principles of Distributed Machine Learning on Big Data. CoRR Eric P. Xing, Qirong Ho, Pengtao Xie, Wei Dai
2015	—	`conf`	The Human Kernel. NIPS Andrew Gordon Wilson, Christoph Dann, Christopher G. Lucas, Eric P. Xing
2015	J	`jnl`	The Human Kernel. CoRR Andrew Gordon Wilson, Christoph Dann, Christopher G. Lucas, Eric P. Xing
2015	—	`conf`	Toward personalized pan-omic association analysis under complex structures and big data. BIBM Eric P. Xing
2014	—	`ch.`	Analyzing Time-Evolving Networks. Handbook of Mixed Membership Models and Their Applications Qirong Ho, Eric P. Xing
2014	A	`conf`	Asymptotically Exact, Embarrassingly Parallel MCMC. UAI Willie Neiswanger, Chong Wang, Eric P. Xing
2014	J	`jnl`	Bayesian inference with posterior regularization and applications to infinite latent SVMs. J. Mach. Learn. Res. Jun Zhu, Ning Chen, Eric P. Xing
2014	J	`jnl`	Cauchy Principal Component Analysis. CoRR Pengtao Xie, Eric P. Xing
2014	J	`jnl`	CryptGraph: Privacy Preserving Graph Analytics on Encrypted Graph. CoRR Pengtao Xie, Eric P. Xing
2014	—	`conf`	Dependent nonparametric trees for dynamic hierarchical clustering. NIPS Kumar Avinava Dubey, Qirong Ho, Sinead A. Williamson, Eric P. Xing
2014	—	`ch.`	Discriminative Training of Mixed Membership Models. Handbook of Mixed Membership Models and Their Applications Jun Zhu, Eric P. Xing
2014	J	`jnl`	Dynamic Language Models for Streaming Text. Trans. Assoc. Comput. Linguistics Dani Yogatama, Chong Wang, Bryan R. Routledge, Noah A. Smith, Eric P. Xing
2014	—	`conf`	Exploiting Bounded Staleness to Speed Up Big Data Analytics. USENIX ATC Henggang Cui, James Cipar, Qirong Ho, Jin Kyu Kim, Seunghak Lee, Abhimanu Kumar, Jinliang Wei, Wei Dai, Gregory R. Ganger, Phillip B. Gibbons, Garth A. Gibson, Eric P. Xing
2014	J	`jnl`	Exploiting Genome Structure in Association Analysis. J. Comput. Biol. Seyoung Kim, Eric P. Xing
2014	—	`conf`	Exploiting iterative-ness for parallel ML computations. SoCC Henggang Cui, Alexey Tumanov, Jinliang Wei, Lianghong Xu, Wei Dai, Jesse Haber-Kucharsky, Qirong Ho, Gregory R. Ganger, Phillip B. Gibbons, Garth A. Gibson, Eric P. Xing
2014	A	`conf`	Fast Distribution To Real Regression. AISTATS Junier B. Oliva, Willie Neiswanger, Barnabás Póczos, Jeff G. Schneider, Eric P. Xing
2014	J	`jnl`	Fast Function to Function Regression. CoRR Junier B. Oliva, Willie Neiswanger, Barnabás Póczos, Eric P. Xing, Jeff G. Schneider
2014	A	`conf`	FlexiFaCT: Scalable Flexible Factorization of Coupled Tensors on Hadoop. SDM Alex Beutel, Partha Pratim Talukdar, Abhimanu Kumar, Christos Faloutsos, Evangelos E. Papalexakis, Eric P. Xing
2014	A	`conf`	Fugue: Slow-Worker-Agnostic Distributed Learning for Big Models on Big Data. AISTATS Abhimanu Kumar, Alex Beutel, Qirong Ho, Eric P. Xing
2014	J	`jnl`	Graph estimation from multi-attribute data. J. Mach. Learn. Res. Mladen Kolar, Han Liu, Eric P. Xing
2014	A*	`conf`	Hierarchical Feature Hashing for Fast Dimensionality Reduction. CVPR Bin Zhao, Eric P. Xing
2014	J	`jnl`	High-Dimensional Feature Selection by Feature-Wise Kernelized Lasso. Neural Comput. Makoto Yamada, Wittawat Jitkrittum, Leonid Sigal, Eric P. Xing, Masashi Sugiyama
2014	J	`jnl`	High-Performance Distributed ML at Scale through Parameter Server Consistency Models. CoRR Wei Dai, Abhimanu Kumar, Jinliang Wei, Qirong Ho, Garth A. Gibson, Eric P. Xing
2014	A*	`conf`	Joint Summarization of Large-Scale Collections of Web Images and Videos for Storyline Reconstruction. CVPR Gunhee Kim, Leonid Sigal, Eric P. Xing
2014	A*	`conf`	Language Modeling with Power Low Rank Ensembles. EMNLP Ankur P. Parikh, Avneesh Saluja, Chris Dyer, Eric P. Xing
2014	J	`jnl`	Large Scale Distributed Distance Metric Learning. CoRR Pengtao Xie, Eric P. Xing
2014	J	`jnl`	Large Scale Distributed Multiclass Logistic Regression. CoRR Pengtao Xie, Jin Kyu Kim, Eric P. Xing
2014	J	`jnl`	LightLDA: Big Topic Models on Modest Compute Clusters. CoRR Jinhui Yuan, Fei Gao, Qirong Ho, Wei Dai, Jinliang Wei, Xun Zheng, Eric P. Xing, Tie-Yan Liu, Wei-Ying Ma
2014	J	`jnl`	Model-Parallel Inference for Big Topic Models. CoRR Xun Zheng, Jin Kyu Kim, Qirong Ho, Eric P. Xing
2014	A	`conf`	Modeling Citation Networks Using Latent Random Offsets. UAI Willie Neiswanger, Chong Wang, Qirong Ho, Eric P. Xing
2014	J	`jnl`	Network Analysis of Breast Cancer Progression and Reversal Using a Tree-Evolving Network Algorithm. PLoS Comput. Biol. Ankur P. Parikh, Ross E. Curtis, Irene Kuhn, Sabine Becker-Weimann, Mina J. Bissell, Eric P. Xing, Wei Wu
2014	—	`conf`	On Model Parallelization and Scheduling Strategies for Distributed Machine Learning. NIPS Seunghak Lee, Jin Kyu Kim, Xun Zheng, Qirong Ho, Garth A. Gibson, Eric P. Xing
2014	—	`conf`	ParLearning Keynote. IPDPS Workshops Eric P. Xing
2014	A	`conf`	Parallel Markov Chain Monte Carlo for Pitman-Yor Mixture Models. UAI Kumar Avinava Dubey, Sinead Williamson, Eric P. Xing
2014	—	`ch.`	Population Stratification with Mixed Membership Models. Handbook of Mixed Membership Models and Their Applications Suyash Shringarpure, Eric P. Xing
2014	J	`jnl`	Primitives for Dynamic Big Model Parallelism. CoRR Seunghak Lee, Jin Kyu Kim, Xun Zheng, Qirong Ho, Garth A. Gibson, Eric P. Xing
2014	A*	`conf`	Quasi Real-Time Summarization for Consumer Videos. CVPR Bin Zhao, Eric P. Xing
2014	A*	`conf`	Reconstructing Storyline Graphs for Image Recommendation from Web Community Photos. CVPR Gunhee Kim, Eric P. Xing
2014	Misc	`conf`	Robust Reverse Engineering of Dynamic Gene Networks Under Sample Size Heterogeneity. Pacific Symposium on Biocomputing Ankur P. Parikh, Wei Wu, Eric P. Xing
2014	J	`jnl`	Screening Rules for Overlapping Group Lasso. CoRR Seunghak Lee, Eric P. Xing
2014	—	`conf`	Sparse sensor selection for nonparametric decentralized detection via L1 regularization. MLSP Weiguang Wang, Yingbin Liang, Eric P. Xing, Lixin Shen
2014	A	`conf`	Spatial compactness meets topical consistency: jointly modeling links and content for community detection. WSDM Mrinmaya Sachan, Avinava Dubey, Shashank Srivastava, Eric P. Xing, Eduard H. Hovy
2014	—	`conf`	Spectral Unsupervised Parsing with Additive Tree Metrics. ACL (1) Ankur P. Parikh, Shay B. Cohen, Eric P. Xing
2014	A	`conf`	The Dependent Dirichlet Process Mixture of Objects for Detection-free Tracking and Object Modeling. AISTATS Willie Neiswanger, Frank D. Wood, Eric P. Xing
2014	A	`conf`	Visualizing brand associations from web community photos. WSDM Gunhee Kim, Eric P. Xing
2013	A	`conf`	A Nonparametric Mixture Model for Topic Modeling over Time. SDM Avinava Dubey, Ahmed Hefny, Sinead Williamson, Eric P. Xing
2013	—	`conf`	A Scalable Approach to Probabilistic Latent Space Inference of Large-Scale Networks. NIPS Junming Yin, Qirong Ho, Eric P. Xing
2013	—	`conf`	An Adaptive Learning Rate for Stochastic Variational Inference. ICML (2) Rajesh Ranganath, Chong Wang, David M. Blei, Eric P. Xing
2013	J	`jnl`	Asymptotically Exact, Embarrassingly Parallel MCMC. CoRR Willie Neiswanger, Chong Wang, Eric P. Xing
2013	A	`conf`	Block Regularized Lasso for Multivariate Multi-Response Linear Regression. AISTATS Weiguang Wang, Yingbin Liang, Eric P. Xing
2013	J	`jnl`	Community Specific Temporal Topic Discovery from Social Media. CoRR Zhiting Hu, Chong Wang, Junjie Yao, Eric P. Xing, Hongzhi Yin, Bin Cui
2013	J	`jnl`	Consistent Bounded-Asynchronous Parameter Servers for Distributed ML. CoRR Jinliang Wei, Wei Dai, Abhimanu Kumar, Xun Zheng, Qirong Ho, Eric P. Xing
2013	—	`conf`	Discovering Pictorial Brand Associations from Large-Scale Online Image Data. ICCV Workshops Gunhee Kim, Eric P. Xing
2013	J	`jnl`	Fast Distribution To Real Regression. CoRR Junier B. Oliva, Willie Neiswanger, Barnabás Póczos, Jeff G. Schneider, Eric P. Xing
2013	A*	`conf`	Fast structure learning in generalized stochastic processes with latent factors. KDD Mohammad Taha Bahadori, Yan Liu, Eric P. Xing
2013	J	`jnl`	GINI: From ISH Images to Gene Interaction Networks. PLoS Comput. Biol. Kriti Puniyani, Eric P. Xing
2013	—	`conf`	Hierarchical Tensor Decomposition of Latent Tree Graphical Models. ICML (3) Le Song, Mariya Ishteva, Ankur P. Parikh, Eric P. Xing, Haesun Park
2013	A	`conf`	Integrating Document Clustering and Topic Modeling. UAI Pengtao Xie, Eric P. Xing
2013	J	`jnl`	Integrating Document Clustering and Topic Modeling. CoRR Pengtao Xie, Eric P. Xing
2013	A*	`conf`	Jointly Aligning and Segmenting Multiple Web Photo Streams for the Inference of Collective Photo Storylines. CVPR Gunhee Kim, Eric P. Xing
2013	J	`jnl`	Language Modeling with Power Low Rank Ensembles. CoRR Ankur P. Parikh, Avneesh Saluja, Chris Dyer, Eric P. Xing
2013	—	`conf`	Markov Network Estimation From Multi-attribute Data. ICML (3) Mladen Kolar, Han Liu, Eric P. Xing
2013	—	`conf`	More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server. NIPS Qirong Ho, James Cipar, Henggang Cui, Seunghak Lee, Jin Kyu Kim, Phillip B. Gibbons, Garth A. Gibson, Gregory R. Ganger, Eric P. Xing
2013	A*	`conf`	Multi-Modal Distance Metric Learning. IJCAI Pengtao Xie, Eric P. Xing
2013	B	`conf`	NP-MuScL: Unsupervised Global Prediction of Interaction Networks from Multiple Data Sources. RECOMB Kriti Puniyani, Eric P. Xing
2013	J	`jnl`	NP-MuScL: Unsupervised Global Prediction of Interaction Networks from Multiple Data Sources. J. Comput. Biol. Kriti Puniyani, Eric P. Xing
2013	—	`conf`	Parallel Markov Chain Monte Carlo for Nonparametric Mixture Models. ICML (1) Sinead Williamson, Avinava Dubey, Eric P. Xing
2013	J	`jnl`	Petuum: A Framework for Iterative-Convergent Distributed ML. CoRR Wei Dai, Jinliang Wei, Xun Zheng, Jin Kyu Kim, Seunghak Lee, Junming Yin, Qirong Ho, Eric P. Xing
2013	—	`conf`	Restricting exchangeable nonparametric distributions. NIPS Sinead Williamson, Steven N. MacEachern, Eric P. Xing
2013	A*	`conf`	Scalable Dynamic Nonparametric Bayesian Models of Content and Users. IJCAI Amr Ahmed, Eric P. Xing
2013	J	`jnl`	Sharp Threshold for Multivariate Multi-Response Linear Regression via Block Regularized Lasso. CoRR Weiguang Wang, Yingbin Liang, Eric P. Xing
2013	A	`conf`	Solving the Straggler Problem with Bounded Staleness. HotOS James Cipar, Qirong Ho, Jin Kyu Kim, Seunghak Lee, Gregory R. Ganger, Garth Gibson, Kimberly Keeton, Eric P. Xing
2013	A*	`conf`	Sparse Output Coding for Large-Scale Visual Recognition. CVPR Bin Zhao, Eric P. Xing
2013	J	`jnl`	Structure-Aware Dynamic Scheduler for Parallel Machine Learning. CoRR Seunghak Lee, Jin Kyu Kim, Qirong Ho, Garth A. Gibson, Eric P. Xing
2013	A	`conf`	Time-sensitive web image ranking and retrieval via dynamic multi-task regression. WSDM Gunhee Kim, Eric P. Xing
2013	—	`conf`	Variance Reduction for Stochastic Gradient Optimization. NIPS Chong Wang, Xi Chen, Alexander J. Smola, Eric P. Xing
2012	J	`jnl`	A Generalized Mean Field Algorithm for Variational Inference in Exponential Families CoRR Eric P. Xing, Michael I. Jordan, Stuart Russell
2012	J	`jnl`	A Spectral Algorithm for Latent Junction Trees CoRR Ankur P. Parikh, Le Song, Mariya Ishteva, Gabi Teodoru, Eric P. Xing
2012	A	`conf`	A Spectral Algorithm for Latent Junction Trees. UAI Ankur P. Parikh, Le Song, Mariya Ishteva, Gabi Teodoru, Eric P. Xing
2012	J	`jnl`	Alternating Directions Dual Decomposition CoRR André F. T. Martins, Mário A. T. Figueiredo, Pedro M. Q. Aguiar, Noah A. Smith, Eric P. Xing
2012	J	`jnl`	Bayesian Inference with Posterior Regularization and Infinite Latent Support Vector Machines CoRR Jun Zhu, Ning Chen, Eric P. Xing
2012	A*	`conf`	Consistent Covariance Selection From Data With Missing Values. ICML Mladen Kolar, Eric P. Xing
2012	A*	`conf`	Document hierarchies from text and links. WWW Qirong Ho, Jacob Eisenstein, Eric P. Xing
2012	J	`jnl`	Enabling dynamic network analysis through visualization in TVNViewer. BMC Bioinform. Ross E. Curtis, Jing Xiang, Ankur P. Parikh, Peter Kinnaird, Eric P. Xing
2012	Misc	`conf`	Finding Genome-Transcriptome-Phenome Associations with Structured Association Mapping and Visualization in GenAMap. Pacific Symposium on Biocomputing Ross E. Curtis, Junming Yin, Peter Kinnaird, Eric P. Xing
2012	J	`jnl`	Graph partition strategies for generalized mean field inference CoRR Eric P. Xing, Michael I. Jordan, Stuart Russell
2012	J	`jnl`	Group Sparse Additive Models CoRR Junming Yin, Xi Chen, Eric P. Xing
2012	A*	`conf`	Group Sparse Additive Models. ICML Junming Yin, Xi Chen, Eric P. Xing
2012	—	`conf`	Inferring Gene Interaction Networks from ISH Images via Kernelized Graphical Models. ECCV (6) Kriti Puniyani, Eric P. Xing
2012	J	`jnl`	Large-Margin Predictive Latent Subspace Learning for Multiview Data Analysis. IEEE Trans. Pattern Anal. Mach. Intell. Ning Chen, Jun Zhu, Fuchun Sun, Eric P. Xing
2012	J	`jnl`	Leveraging input and output structures for joint mapping of epistatic and marginal eQTLs. Bioinform. Seunghak Lee, Eric P. Xing
2012	J	`jnl`	Mapping the geographical diffusion of new words CoRR Jacob Eisenstein, Brendan O'Connor, Noah A. Smith, Eric P. Xing
2012	J	`jnl`	MedLDA: maximum margin supervised topic models. J. Mach. Learn. Res. Jun Zhu, Amr Ahmed, Eric P. Xing
2012	J	`jnl`	Mining Associated Text and Images with Dual-Wing Harmoniums CoRR Eric P. Xing, Rong Yan, Alexander G. Hauptmann
2012	—	`conf`	Monte Carlo Methods for Maximum Margin Supervised Topic Models. NIPS Qixia Jiang, Jun Zhu, Maosong Sun, Eric P. Xing
2012	—	`conf`	Multi-Level Structured Image Coding on High-Dimensional Image Representation. ACCV (2) Li-Jia Li, Jun Zhu, Hao Su, Eric P. Xing, Li Fei-Fei
2012	B	`conf`	Nonparametric decentralized detection based on weighted count kernel. ISIT Jiayao Hu, Yingbin Liang, Eric P. Xing
2012	—	`conf`	On Triangular versus Edge Representations --- Towards Scalable Modeling of Networks. NIPS Qirong Ho, Junming Yin, Eric P. Xing
2012	A*	`conf`	On multiple foreground cosegmentation. CVPR Gunhee Kim, Eric P. Xing
2012	J	`jnl`	Smoothing Proximal Gradient Method for General Structured Sparse Learning CoRR Xi Chen, Qihang Lin, Seyoung Kim, Jaime G. Carbonell, Eric P. Xing
2012	J	`jnl`	Sparse Topical Coding CoRR Jun Zhu, Eric P. Xing
2012	A*	`conf`	Supervised Probabilistic Robust Embedding with Sparse Noise. AAAI Yu Zhang, Dit-Yan Yeung, Eric P. Xing
2012	—	`conf`	Symmetric Correspondence Topic Models for Multilingual Text Analysis. NIPS Kosuke Fukumasu, Koji Eguchi, Eric P. Xing
2012	J	`jnl`	Timeline: A Dynamic Hierarchical Dirichlet Process Model for Recovering Birth/Death and Evolution of Topics in Text Stream CoRR Amr Ahmed, Eric P. Xing
2012	—	`conf`	Topic Models, Latent Space Models, Sparse Coding, and All That: A Systematic Understanding of Probabilistic Semantic Extraction in Large Corpus. ACL (Tutorial Abstracts) Eric P. Xing
2012	—	`conf`	TopicViz: interactive topic exploration in document collections. CHI Extended Abstracts Jacob Eisenstein, Duen Horng Chau, Aniket Kittur, Eric P. Xing
2012	J	`jnl`	Understanding the Interaction between Interests, Conversations and Friendships in Facebook CoRR Qirong Ho, Rong Yan, Rajat Raina, Eric P. Xing
2012	A*	`conf`	Web image prediction using multivariate point processes. KDD Gunhee Kim, Li Fei-Fei, Eric P. Xing
2011	A*	`conf`	A Spectral Algorithm for Latent Tree Graphical Models. ICML Ankur P. Parikh, Le Song, Eric P. Xing
2011	A*	`conf`	An Augmented Lagrangian Approach to Constrained MAP Inference. ICML André F. T. Martins, Mário A. T. Figueiredo, Pedro M. Q. Aguiar, Noah A. Smith, Eric P. Xing
2011	A*	`conf`	Approximating Correlated Equilibria using Relaxations on the Marginal Polytope. ICML Hetunandan Kamisetty, Eric P. Xing, Christopher James Langmead
2011	A*	`conf`	Conditional topical coding: an efficient topic model conditioned on rich features. KDD Jun Zhu, Ni Lao, Ning Chen, Eric P. Xing
2011	A*	`conf`	Discovering Sociolinguistic Associations with Structured Sparsity. ACL Jacob Eisenstein, Noah A. Smith, Eric P. Xing
2011	A*	`conf`	Distributed cosegmentation via submodular optimization on anisotropic diffusion. ICCV Gunhee Kim, Eric P. Xing, Li Fei-Fei, Takeo Kanade
2011	A	`conf`	Evolving Cluster Mixed-Membership Blockmodel for Time-Evolving Networks. AISTATS Qirong Ho, Le Song, Eric P. Xing
2011	—	`conf`	GenAMap: Visualization strategies for structured association mapping. BioVis Ross E. Curtis, Peter Kinnaird, Eric P. Xing
2011	—	`conf`	Genome-Phenome Association Analysis of Complex Diseases a Structured Sparse Regression Approach - (Keynote Talk). ISBRA Eric P. Xing
2011	—	`conf`	Infinite Latent SVM for Classification and Multi-task Learning. NIPS Jun Zhu, Ning Chen, Eric P. Xing
2011	A*	`conf`	Infinite SVM: a Dirichlet Process Mixture of Large-margin Kernel Machines. ICML Jun Zhu, Ning Chen, Eric P. Xing
2011	—	`conf`	Kernel Embeddings of Latent Tree Graphical Models. NIPS Le Song, Ankur P. Parikh, Eric P. Xing
2011	—	`conf`	Large-Scale Category Structure Aware Image Categorization. NIPS Bin Zhao, Li Fei-Fei, Eric P. Xing
2011	A	`conf`	Max margin learning on domain-independent web information extraction. CIKM Bin Zhao, Xiaoxin Yin, Eric P. Xing
2011	A	`conf`	Multiscale Community Blockmodel for Network Exploration. AISTATS Qirong Ho, Ankur P. Parikh, Le Song, Eric P. Xing
2011	—	`conf`	Nonparametric decision making based on tree-structured information aggregation. Allerton Jiayao Hu, Yingbin Liang, Eric P. Xing
2011	A	`conf`	On Time Varying Undirected Graphs. AISTATS Mladen Kolar, Eric P. Xing
2011	A	`conf`	Online Inference for the Infinite Topic-Cluster Model: Storylines from Streaming Text. AISTATS Amr Ahmed, Qirong Ho, Choon Hui Teo, Jacob Eisenstein, Alexander J. Smola, Eric P. Xing
2011	A	`conf`	Online Learning of Structured Predictors with Multiple Kernels. AISTATS André Filipe Torres Martins, Noah A. Smith, Eric P. Xing, Pedro M. Q. Aguiar, Mário A. T. Figueiredo
2011	A*	`conf`	Online detection of unusual events in videos via dynamic sparse coding. CVPR Bin Zhao, Li Fei-Fei, Eric P. Xing
2011	A	`conf`	Smoothing Proximal Gradient Method for General Structured Sparse Learning. UAI Xi Chen, Qihang Lin, Seyoung Kim, Jaime G. Carbonell, Eric P. Xing
2011	A*	`conf`	Sparse Additive Generative Models of Text. ICML Jacob Eisenstein, Amr Ahmed, Eric P. Xing
2011	A	`conf`	Sparse Topical Coding. UAI Jun Zhu, Eric P. Xing
2011	J	`jnl`	StructHDP: automatic inference of number of clusters and population structure from admixed genotype data. Bioinform. Suyash Shringarpure, Daegun Won, Eric P. Xing
2011	—	`conf`	Structured Databases of Named Entities from Bayesian Nonparametrics. ULNLP@EMNLP Jacob Eisenstein, Tae Yano, William W. Cohen, Noah A. Smith, Eric P. Xing
2011	J	`jnl`	TREEGL: reverse engineering tree-evolving gene networks underlying developing biological lineages. Bioinform. Ankur P. Parikh, Wei Wu, Ross E. Curtis, Eric P. Xing
2011	J	`jnl`	TVNViewer: An interactive visualization tool for exploring networks that change over time or space. Bioinform. Ross E. Curtis, Amos Yuen, Le Song, Anuj Goyal, Eric P. Xing
2011	J	`jnl`	TopicScape: Semantic Navigation of Document Collections CoRR Jacob Eisenstein, Duen Horng Chau, Aniket Kittur, Eric P. Xing
2011	A*	`conf`	Unified analysis of streaming news. WWW Amr Ahmed, Qirong Ho, Jacob Eisenstein, Eric P. Xing, Alexander J. Smola, Choon Hui Teo
2010	A*	`conf`	A Latent Variable Model for Geographic Lexical Variation. EMNLP Jacob Eisenstein, Brendan O'Connor, Noah A. Smith, Eric P. Xing
2010	—	`conf`	Adaptive Multi-Task Lasso: with Application to eQTL Detection. NIPS Seunghak Lee, Jun Zhu, Eric P. Xing
2010	J	`jnl`	An Efficient Proximal-Gradient Method for Single and Multi-task Regression with Structured Sparsity CoRR Xi Chen, Qihang Lin, Seyoung Kim, Javier Peña, Jaime G. Carbonell, Eric P. Xing
2010	A*	`conf`	Conditional Topic Random Fields. ICML Jun Zhu, Eric P. Xing
2010	A*	`conf`	Grafting-light: fast, incremental feature selection and structure learning of Markov random fields. KDD Jun Zhu, Ni Lao, Eric P. Xing
2010	J	`jnl`	Graph-Structured Multi-task Regression and an Efficient Optimization Method for General Fused Lasso CoRR Xi Chen, Seyoung Kim, Qihang Lin, Jaime G. Carbonell, Eric P. Xing
2010	—	`conf`	Image Segmentation with Topic Random Field. ECCV (5) Bin Zhao, Li Fei-Fei, Eric P. Xing
2010	—	`conf`	Large Margin Learning of Upstream Scene Understanding Models. NIPS Jun Zhu, Li-Jia Li, Li Fei-Fei, Eric P. Xing
2010	B	`conf`	MoGUL: Detecting Common Insertions and Deletions in a Population. RECOMB Seunghak Lee, Eric P. Xing, Michael Brudno
2010	—	`conf`	Modeling and Analysis of Dynamic Behaviors of Web Image Collections. ECCV (5) Gunhee Kim, Eric P. Xing, Antonio Torralba
2010	J	`jnl`	Multi-population GWA mapping via multi-task regularized regression. Bioinform. Kriti Puniyani, Seyoung Kim, Eric P. Xing
2010	—	`conf`	Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification. NIPS Li-Jia Li, Hao Su, Eric P. Xing, Li Fei-Fei
2010	A*	`conf`	On Sparse Nonparametric Conditional Covariance Selection. ICML Mladen Kolar, Ankur P. Parikh, Eric P. Xing
2010	—	`conf`	Predictive Subspace Learning for Multi-view Data: a Large Margin Approach. NIPS Ning Chen, Jun Zhu, Eric P. Xing
2010	J	`jnl`	SPEX Bioinform. Kriti Puniyani, Christos Faloutsos, Eric P. Xing
2010	A*	`conf`	Staying Informed: Supervised and Semi-Supervised Multi-View Topical Analysis of Ideological Perspective. EMNLP Amr Ahmed, Eric P. Xing
2010	J	`jnl`	Structured literature image finder: Parsing text and figures in biomedical literature. J. Web Semant. Amr Ahmed, Andrew Arnold, Luís Pedro Coelho, Joshua D. Kangas, Abdul-Saboor Sheikh, Eric P. Xing, William W. Cohen, Robert F. Murphy
2010	A	`conf`	Timeline: A Dynamic Hierarchical Dirichlet Process Model for Recovering Birth/Death and Evolution of Topics in Text Stream. UAI Amr Ahmed, Eric P. Xing
2010	A*	`conf`	Tree-Guided Group Lasso for Multi-Task Regression with Structured Sparsity. ICML Seyoung Kim, Eric P. Xing
2010	A*	`conf`	Turbo Parsers: Dependency Parsing by Approximate Variational Inference. EMNLP André F. T. Martins, Noah A. Smith, Eric P. Xing, Pedro M. Q. Aguiar, Mário A. T. Figueiredo
2010	A	`conf`	Ultra-high Dimensional Multiple Output Learning With Simultaneous Orthogonal Matching Pursuit: Screening Approach. AISTATS Mladen Kolar, Eric P. Xing
2009	J	`jnl`	A multivariate regression approach to association analysis of a quantitative trait network. Bioinform. Seyoung Kim, Kyung-Ah Sohn, Eric P. Xing
2009	—	`conf`	Concise Integer Linear Programming Formulations for Dependency Parsing. ACL/IJCNLP André F. T. Martins, Noah A. Smith, Eric P. Xing
2009	J	`jnl`	DISCOVER: a feature-based discriminative method for motif search in complex genomes. Bioinform. Wenjie Fu, Pradipta Ray, Eric P. Xing
2009	A*	`conf`	Dynamic mixed membership blockmodel for evolving networks. ICML Wenjie Fu, Le Song, Eric P. Xing
2009	—	`conf`	Heterogeneous multitask learning with joint sparsity constraints. NIPS Xiaolin Yang, Seyoung Kim, Eric P. Xing
2009	J	`jnl`	KELLER: estimating time-varying interactions between genes. Bioinform. Le Song, Mladen Kolar, Eric P. Xing
2009	J	`jnl`	Maximum Entropy Discrimination Markov Networks. J. Mach. Learn. Res. Jun Zhu, Eric P. Xing
2009	A*	`conf`	MedLDA: maximum margin supervised topic models for regression and classification. ICML Jun Zhu, Amr Ahmed, Eric P. Xing
2009	A	`conf`	Network Completion and Survey Sampling. AISTATS Steve Hanneke, Eric P. Xing
2009	J	`jnl`	Nonextensive Information Theoretic Kernels on Measures. J. Mach. Learn. Res. André F. T. Martins, Noah A. Smith, Eric P. Xing, Pedro M. Q. Aguiar, Mário A. T. Figueiredo
2009	A*	`conf`	On primal and dual sparsity of Markov networks. ICML Jun Zhu, Eric P. Xing
2009	A*	`conf`	Polyhedral outer approximations with application to natural language parsing. ICML André F. T. Martins, Noah A. Smith, Eric P. Xing
2009	A*	`conf`	Primal sparse Max-margin Markov networks. KDD Jun Zhu, Eric P. Xing, Bo Zhang
2009	—	`conf`	Sparsistent Learning of Varying-coefficient Models with Structural Changes. NIPS Mladen Kolar, Le Song, Eric P. Xing
2009	A*	`conf`	Structured correspondence topic models for mining captioned figures in biological literature. KDD Amr Ahmed, Eric P. Xing, William W. Cohen, Robert F. Murphy
2009	—	`conf`	Time-Varying Dynamic Bayesian Networks. NIPS Le Song, Mladen Kolar, Eric P. Xing
2008	—	`conf`	A Joint Topic and Perspective Model for Ideological Discourse. ECML/PKDD (2) Wei-Hao Lin, Eric P. Xing, Alexander G. Hauptmann
2008	B	`conf`	BayCis: A Bayesian Hierarchical HMM for Cis-Regulatory Module Decoding in Metazoan Genomes. RECOMB Tien-ho Lin, Pradipta Ray, Geir Kjetil Sandve, Selen Uguroglu, Eric P. Xing
2008	J	`jnl`	C-DEM: a multi-modal query system for Drosophila Embryo databases. Proc. VLDB Endow. Fan Guo, Lei Li, Christos Faloutsos, Eric P. Xing
2008	J	`jnl`	CSMET: Comparative Genomic Motif Detection via Multi-Resolution Phylogenetic Shadowing. PLoS Comput. Biol. Pradipta Ray, Suyash Shringarpure, Mladen Kolar, Eric P. Xing
2008	A	`conf`	Dynamic Non-Parametric Mixture Models and the Recurrent Chinese Restaurant Process: with Applications to Evolutionary Clustering. SDM Amr Ahmed, Eric P. Xing
2008	A	`conf`	Feature Selection via Block-Regularized Regression. UAI Seyoung Kim, Eric P. Xing
2008	J	`jnl`	Free Energy Estimates of All-Atom Protein Structures Using Generalized Belief Propagation. J. Comput. Biol. Hetunandan Kamisetty, Eric P. Xing, Christopher James Langmead
2008	J	`jnl`	Harmonium Models for Video Classification. Stat. Anal. Data Min. Jun Yang, Rong Yan, Yan Liu, Eric P. Xing
2008	A*	`conf`	Joint latent topic models for text and citations. KDD Ramesh Nallapati, Amr Ahmed, Eric P. Xing, William W. Cohen
2008	A*	`conf`	Laplace maximum margin Markov networks. ICML Jun Zhu, Eric P. Xing, Bo Zhang
2008	—	`conf`	Mixed Membership Stochastic Blockmodels. NIPS Edoardo M. Airoldi, David M. Blei, Stephen E. Fienberg, Eric P. Xing
2008	J	`jnl`	Mixed Membership Stochastic Blockmodels. J. Mach. Learn. Res. Edoardo M. Airoldi, David M. Blei, Stephen E. Fienberg, Eric P. Xing
2008	A*	`conf`	Nonextensive entropic kernels. ICML André F. T. Martins, Mário A. T. Figueiredo, Pedro M. Q. Aguiar, Noah A. Smith, Eric P. Xing
2008	—	`conf`	Partially Observed Maximum Entropy Discrimination Markov Networks. NIPS Jun Zhu, Eric P. Xing, Bo Zhang
2008	A	`conf`	Semi-Supervised Learning Based on Semiparametric Regularization. SDM Zhen Guo, Zhongfei (Mark) Zhang, Eric P. Xing, Christos Faloutsos
2008	A*	`conf`	Stacking Dependency Parsers. EMNLP André F. T. Martins, Dipanjan Das, Noah A. Smith, Eric P. Xing
2008	—	`conf`	Structured Literature Image Finder: Extracting Information from Text and Images in Biomedical Literature. BioLINK@ISMB/ECCB Luís Pedro Coelho, Amr Ahmed, Andrew Arnold, Joshua D. Kangas, Abdul-Saboor Sheikh, Eric P. Xing, William W. Cohen, Robert F. Murphy
2008	—	`conf`	Training Hierarchical Feed-Forward Visual Recognition Models Using Transfer Learning from Pseudo-Tasks. ECCV (3) Amr Ahmed, Kai Yu, Wei Xu, Yihong Gong, Eric P. Xing
2007	A	`conf`	A Max Margin Framework on Image Annotation and Multimodal Image Retrieval. ICME Zhen Guo, Zhongfei Zhang, Eric P. Xing, Christos Faloutsos
2007	J	`jnl`	Bayesian Haplotype Inference via the Dirichlet Process. J. Comput. Biol. Eric P. Xing, Michael I. Jordan, Roded Sharan
2007	A*	`conf`	Enhanced max margin learning on multimodal data mining in a multimedia database. KDD Zhen Guo, Zhongfei Zhang, Eric P. Xing, Christos Faloutsos
2007	A	`conf`	Feature selection for grasp recognition from optical markers. IROS Lillian Y. Chang, Nancy S. Pollard, Tom M. Mitchell, Eric P. Xing
2007	B	`conf`	Free Energy Estimates of All-Atom Protein Structures Using Generalized Belief Propagation. RECOMB Hetunandan Kamisetty, Eric P. Xing, Christopher James Langmead
2007	B	`conf`	GIMscan: A New Statistical Method for Analyzing Whole-Genome Array CGH Data. RECOMB Yanxin Shi, Fan Guo, Wei Wu, Eric P. Xing
2007	—	`conf`	HM-BiTAM: Bilingual Topic Exploration, Word Alignment, and Translation. NIPS Bing Zhao, Eric P. Xing
2007	A	`conf`	Harmonium Models for Semantic Video Representation and Classification. SDM Jun Yang, Yan Liu, Eric P. Xing, Alexander G. Hauptmann
2007	A*	`conf`	Learning GMRF Structures for Spatial Priors. CVPR Lie Gu, Eric P. Xing, Takeo Kanade
2007	J	`jnl`	Mixed membership stochastic blockmodels. CoRR Edoardo M. Airoldi, David M. Blei, Stephen E. Fienberg, Eric P. Xing
2007	C	`conf`	Probabilistic Graphical Models-Theory, Algorithm, and Application. ICMLA Eric P. Xing
2007	A*	`conf`	Recovering temporally rewiring networks: a model-based approach. ICML Fan Guo, Steve Hanneke, Wenjie Fu, Eric P. Xing
2007	A	`conf`	Seeking The Truly Correlated Topic Posterior - on tight approximate inference of logistic-normal admixture model. AISTATS Amr Ahmed, Eric P. Xing
2007	—	`conf`	Sparse Word Graphs: A Scalable Algorithm for Capturing Word Correlations in Topic Models. ICDM Workshops Ramesh Nallapati, Amr Ahmed, William W. Cohen, Eric P. Xing
2007	—	`ed.`	Statistical Network Analysis: Models, Issues, and New Directions - ICML 2006 Workshop on Statistical Network Analysis, Pittsburgh, PA, USA, June 29, 2006, Revised Selected Papers SNA@ICML Edoardo M. Airoldi, David M. Blei, Stephen E. Fienberg, Anna Goldenberg, Eric P. Xing, Alice X. Zheng
2006	A*	`conf`	Automatic mining of fruit fly embryo images. KDD Jia-Yu Pan, André G. R. Balan, Eric P. Xing, Agma J. M. Traina, Christos Faloutsos
2006	A*	`conf`	Bayesian multi-population haplotype inference via a hierarchical dirichlet process mixture. ICML Eric P. Xing, Kyung-Ah Sohn, Michael I. Jordan, Yee Whye Teh
2006	A*	`conf`	BiTAM: Bilingual Topic AdMixture Models for Word Alignment. ACL Bing Zhao, Eric P. Xing
2006	—	`conf`	Combining Stochastic Block Models and Mixed Membership for Statistical Network Analysis. SNA@ICML Edoardo M. Airoldi, David M. Blei, Stephen E. Fienberg, Eric P. Xing
2006	—	`conf`	Discrete Temporal Models of Social Networks. SNA@ICML Steve Hanneke, Eric P. Xing
2006	—	`conf`	Hidden Markov Dirichlet Process: Modeling Genetic Recombination in Open Ancestral Space. NIPS Kyung-Ah Sohn, Eric P. Xing
2006	—	`conf`	Interpreting anonymous DNA samples from mass disasters - probabilistic forensic inference using genetic markers. ISMB (Supplement of Bioinformatics) Tien-ho Lin, Eugene W. Myers, Eric P. Xing
2005	—	`conf`	A latent mixed membership model for relational data. LinkKDD Edoardo M. Airoldi, David M. Blei, Eric P. Xing, Stephen E. Fienberg
2005	—	`conf`	Bilingual Word Spectral Clustering for Statistical Machine Translation. ParallelText@ACL Bing Zhao, Eric P. Xing, Alex Waibel
2005	J	`jnl`	Comparison of normalization methods for CodeLink Bioarray data. BMC Bioinform. Wei Wu, Nilesh Dave, George C. Tseng, Thomas Richards, Eric P. Xing, Naftali Kaminski
2005	J	`jnl`	Evaluation of normalization methods for cDNA microarray data by BMC Bioinform. Wei Wu, Eric P. Xing, Connie Myers, I. Saira Mian, Mina J. Bissell
2005	—	`conf`	From Lasso regression to Feature vector machine. NIPS Fan Li, Yiming Yang, Eric P. Xing
2005	A	`conf`	Mining Associated Text and Images with Dual-Wing Harmoniums. UAI Eric P. Xing, Rong Yan, Alexander G. Hauptmann
2005	A*	`conf`	Predicting protein folds with structural repeats using a chain graph model. ICML Yan Liu, Eric P. Xing, Jaime G. Carbonell
2004	A*	`conf`	Bayesian haplo-type inference via the dirichlet process. ICML Eric P. Xing, Roded Sharan, Michael I. Jordan
2004	A	`conf`	Graph Partition Strategies for Generalized Mean Field Inference. UAI Eric P. Xing, Michael I. Jordan
2004	J	`jnl`	Logos: a Modular Bayesian Model for J. Bioinform. Comput. Biol. Eric P. Xing, Wei Wu, Michael I. Jordan, Richard M. Karp
2004	J	`jnl`	MotifPrototyper: A Bayesian profile model for motif families. Proc. Natl. Acad. Sci. USA Eric P. Xing, Richard M. Karp
2003	A	`conf`	A generalized mean field algorithm for variational inference in exponential families. UAI Eric P. Xing, Michael I. Jordan, Stuart Russell
2003	—	`conf`	LOGOS: a modular Bayesian model for de novo motif detection. CSB Eric P. Xing, Wei Wu, Michael I. Jordan, Richard M. Karp
2002	—	`conf`	A Hierarchical Bayesian Markovian Model for Motifs in Biopolymer Sequences. NIPS Eric P. Xing, Michael I. Jordan, Richard M. Karp, Stuart Russell
2002	—	`conf`	Distance Metric Learning with Application to Clustering with Side-Information. NIPS Eric P. Xing, Andrew Y. Ng, Michael I. Jordan, Stuart Russell
2001	—	`conf`	CLIFF: clustering of high-dimensional microarray data via iterative feature filtering using normalized cuts. ISMB (Supplement of Bioinformatics) Eric P. Xing, Richard M. Karp
2001	A*	`conf`	Feature selection for high-dimensional genomic microarray data. ICML Eric P. Xing, Michael I. Jordan, Richard M. Karp