Tong Zhang - RankMe

666 papers A* 171A 6B 9Misc 1Journal 386Unranked 89

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	GT-SVJ: Generative-Transformer-Based Self-Supervised Video Judge For Efficient Video Reward Modeling. CoRR Shivanshu Shekhar, Uttaran Bhattacharya, Raghavendra Addanki, Md. Mehrab Tanjim, Somdeb Sarkhel, Tong Zhang
2026	J	`jnl`	GUI-Libra: Training Native GUI Agents to Reason and Act with Action-aware Supervision and Partially Verifiable RL. CoRR Rui Yang, Qianhui Wu, Zhaoyang Wang, Hanyang Chen, Ke Yang, Hao Cheng, Huaxiu Yao, Baoling Peng, Huan Zhang, Jianfeng Gao, Tong Zhang
2026	J	`jnl`	PMGT-VR: A Decentralized Proximal-Gradient Algorithmic Framework With Variance Reduction. IEEE Trans. Pattern Anal. Mach. Intell. Haishan Ye, Wei Xiong, Tong Zhang
2026	J	`jnl`	PRL: Process Reward Learning Improves LLMs' Reasoning Ability and Broadens the Reasoning Boundary. CoRR Jiarui Yao, Ruida Wang, Tong Zhang
2026	J	`jnl`	PhysProver: Advancing Automatic Theorem Proving for Physics. CoRR Hanning Zhang, Ruida Wang, Rui Pan, Wenyuan Wang, BingXu Meng, Tong Zhang
2026	J	`jnl`	Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training. Trans. Mach. Learn. Res. Yangyi Chen, Hao Peng, Tong Zhang, Heng Ji
2026	—	`conf`	Tackling Distractor Documents in Multi-Hop QA with Reinforcement and Curriculum Learning. EACL (Findings) Jerry Huang, Siddarth Madala, Risham Sidhu, Cheng Niu, Hao Peng, Julia Hockenmaier, Tong Zhang
2026	J	`jnl`	WebGym: Scaling Training Environments for Visual Web Agents with Realistic Tasks. CoRR Hao Bai, Alexey Taymanov, Tong Zhang, Aviral Kumar, Spencer Whitehead
2025	J	`jnl`	A Minimalist Approach to LLM Reasoning: from Rejection Sampling to Reinforce. CoRR Wei Xiong, Jiarui Yao, Yuhui Xu, Bo Pang, Lei Wang, Doyen Sahoo, Junnan Li, Nan Jiang, Tong Zhang, Caiming Xiong, Hanze Dong
2025	J	`jnl`	A Sharp KL-Convergence Analysis for Diffusion Models under Minimal Assumptions. CoRR Nishant Jain, Tong Zhang
2025	J	`jnl`	ASGO: Adaptive Structured Gradient Optimization. CoRR Kang An, Yuxing Liu, Rui Pan, Shiqian Ma, Donald Goldfarb, Tong Zhang
2025	A*	`conf`	AdaGrad under Anisotropic Smoothness. ICLR Yuxing Liu, Rui Pan, Tong Zhang
2025	J	`jnl`	Adapt-Pruner: Adaptive Structural Pruning for Efficient Small Language Model Training. CoRR Boyao Wang, Rui Pan, Shizhe Diao, Xingyuan Pan, Jipeng Zhang, Renjie Pi, Tong Zhang
2025	J	`jnl`	Almost Linear Convergence under Minimal Score Assumptions: Quantized Transition Diffusion. CoRR Xunpeng Huang, Yingyu Lin, Nikki Lijing Kuang, Hanze Dong, Difan Zou, Yian Ma, Tong Zhang
2025	J	`jnl`	Beyond Correctness: Harmonizing Process and Outcome Rewards through RL Training. CoRR Chenlu Ye, Zhou Yu, Ziji Zhang, Hao Chen, Narayanan Sadagopan, Jing Huang, Tong Zhang, Anurag Beniwal
2025	—	`conf`	Bridge-Coder: Transferring Model Capabilities from High-Resource to Low-Resource Programming Language. ACL (Findings) Jipeng Zhang, Jianshu Zhang, Yuanzhe Li, Renjie Pi, Rui Pan, Runtao Liu, Ziqiang Zheng, Tong Zhang
2025	A*	`conf`	Building Math Agents with Multi-Turn Iterative Preference Learning. ICLR Wei Xiong, Chengshuai Shi, Jiaming Shen, Aviv Rosenberg, Zhen Qin, Daniele Calandriello, Misha Khalman, Rishabh Joshi, Bilal Piot, Mohammad Saleh, Chi Jin, Tong Zhang, Tianqi Liu
2025	J	`jnl`	CAPTAIN: Semantic Feature Injection for Memorization Mitigation in Text-to-Image Diffusion Models. CoRR Tong Zhang, Carlos Hinojosa, Bernard Ghanem
2025	J	`jnl`	Capturing Conditional Dependence via Auto-regressive Diffusion Models. CoRR Xunpeng Huang, Yujin Han, Difan Zou, Yian Ma, Tong Zhang
2025	A*	`conf`	Catoni Contextual Bandits are Robust to Heavy-tailed Rewards. ICML Chenlu Ye, Yujia Jin, Alekh Agarwal, Tong Zhang
2025	J	`jnl`	Catoni Contextual Bandits are Robust to Heavy-tailed Rewards. CoRR Chenlu Ye, Yujia Jin, Alekh Agarwal, Tong Zhang
2025	J	`jnl`	Chain-of-Experts: Unlocking the Communication Power of Mixture-of-Experts Models. CoRR Zihan Wang, Rui Pan, Jiarui Yao, Robert Csordas, Linjie Li, Lu Yin, Jiajun Wu, Tong Zhang, Manling Li, Shiwei Liu
2025	J	`jnl`	Contextual Relevance and Adaptive Sampling for LLM-Based Document Reranking. CoRR Jerry Huang, Siddarth Madala, Cheng Niu, Julia Hockenmaier, Tong Zhang
2025	J	`jnl`	Daunce: Data Attribution through Uncertainty Estimation. CoRR Xingyuan Pan, Chenlu Ye, Joseph Melkonian, Jiaqi W. Ma, Tong Zhang
2025	J	`jnl`	DuaShepherd: Integrating Stepwise Correctness and Potential Rewards for Mathematical Reasoning. CoRR Yuanhao Wu, Juntong Song, Hanning Zhang, Tong Zhang, Cheng Niu
2025	J	`jnl`	ERA: Transforming VLMs into Embodied Agents via Embodied Prior Learning and Online Reinforcement Learning. CoRR Hanyang Chen, Mark Zhao, Rui Yang, Qinwei Ma, Ke Yang, Jiarui Yao, Kangrui Wang, Hao Bai, Zhenhailong Wang, Rui Pan, Mengchao Zhang, Jose A. Barreiros, Aykut Özgün Önol, ChengXiang Zhai, Heng Ji, Manling Li, Huan Zhang, Tong Zhang
2025	A*	`conf`	EmbodiedBench: Comprehensive Benchmarking Multi-modal Large Language Models for Vision-Driven Embodied Agents. ICML Rui Yang, Hanyang Chen, Junyu Zhang, Mark Zhao, Cheng Qian, Kangrui Wang, Qineng Wang, Teja Venkat Koripella, Marziyeh Movahedi, Manling Li, Heng Ji, Huan Zhang, Tong Zhang
2025	J	`jnl`	EmbodiedBench: Comprehensive Benchmarking Multi-modal Large Language Models for Vision-Driven Embodied Agents. CoRR Rui Yang, Hanyang Chen, Junyu Zhang, Mark Zhao, Cheng Qian, Kangrui Wang, Qineng Wang, Teja Venkat Koripella, Marziyeh Movahedi, Manling Li, Heng Ji, Huan Zhang, Tong Zhang
2025	J	`jnl`	Entropy-Regularized Process Reward Model. Trans. Mach. Learn. Res. Hanning Zhang, Pengcheng Wang, Shizhe Diao, Yong Lin, Rui Pan, Hanze Dong, Dylan Zhang, Pavlo Molchanov, Tong Zhang
2025	J	`jnl`	FourCastLSTM: A precipitation nowcasting model integrating global and local spatiotemporal features. Comput. Geosci. Chuangwei Xu, Jie Liu, Shiyuan Han, Xiaoqi Duan, Lei Xiang, Tong Zhang
2025	—	`conf`	From Lists to Emojis: How Format Bias Affects Model Alignment. ACL (1) Xuanchang Zhang, Wei Xiong, Lichang Chen, Tianyi Zhou, Heng Huang, Tong Zhang
2025	J	`jnl`	Fully First-Order Methods for DecentralizedBilevel Optimization. IEEE Trans. Signal Process. Xiaoyu Wang, Xuxing Chen, Shiqian Ma, Tong Zhang
2025	J	`jnl`	GAR: Generative Adversarial Reinforcement Learning for Formal Theorem Proving. CoRR Ruida Wang, Jiarui Yao, Rui Pan, Shizhe Diao, Tong Zhang
2025	J	`jnl`	GUI-Actor: Coordinate-Free Visual Grounding for GUI Agents. CoRR Qianhui Wu, Kanzhi Cheng, Rui Yang, Chaoyun Zhang, Jianwei Yang, Huiqiang Jiang, Jian Mu, Baolin Peng, Bo Qiao, Reuben Tan, Si Qin, Lars Liden, Qingwei Lin, Huan Zhang, Tong Zhang, Jianbing Zhang, Dongmei Zhang, Jianfeng Gao
2025	J	`jnl`	GUIDE: Towards Scalable Advising for Research Ideas. CoRR Yaowenqi Liu, BingXu Meng, Rui Pan, Jerry Huang, Tong Zhang
2025	J	`jnl`	Generalizable Geometric Image Caption Synthesis. CoRR Yue Xin, Wenyuan Wang, Rui Pan, Ruida Wang, Howard Meng, Renjie Pi, Shizhe Diao, Tong Zhang
2025	J	`jnl`	Hessian-Aware Zeroth-Order Optimization. IEEE Trans. Pattern Anal. Mach. Intell. Haishan Ye, Zhichao Huang, Cong Fang, Chris Junchi Li, Tong Zhang
2025	J	`jnl`	Language-Driven Visual Consensus for Zero-Shot Semantic Segmentation. IEEE Trans. Circuits Syst. Video Technol. Zicheng Zhang, Wei Ke, Yi Zhu, Xiaodan Liang, Jianzhuang Liu, Qixiang Ye, Tong Zhang
2025	J	`jnl`	Lean4Physics: Comprehensive Reasoning Framework for College-level Physics in Lean4. CoRR Yuxin Li, Minghao Liu, Ruida Wang, Wenzhao Ji, Zhitao He, Rui Pan, Junming Huang, Tong Zhang, Yi R. Fung
2025	A*	`conf`	Let's Reason Formally: Natural-Formal Hybrid Reasoning Enhances LLM's Math Capability. EMNLP Ruida Wang, Yuxin Li, Yi R. Fung, Tong Zhang
2025	J	`jnl`	Let's Reason Formally: Natural-Formal Hybrid Reasoning Enhances LLM's Math Capability. CoRR Ruida Wang, Yuxin Li, Yi R. (May) Fung, Tong Zhang
2025	J	`jnl`	Localize-and-Stitch: Efficient Model Merging via Sparse Task Arithmetic. Trans. Mach. Learn. Res. Yifei He, Yuzheng Hu, Yong Lin, Tong Zhang, Han Zhao
2025	A*	`conf`	Logarithmic Regret for Online KL-Regularized Reinforcement Learning. ICML Heyang Zhao, Chenlu Ye, Wei Xiong, Quanquan Gu, Tong Zhang
2025	J	`jnl`	Logarithmic Regret for Online KL-Regularized Reinforcement Learning. CoRR Heyang Zhao, Chenlu Ye, Wei Xiong, Quanquan Gu, Tong Zhang
2025	A*	`conf`	MA-LoT: Model-Collaboration Lean-based Long Chain-of-Thought Reasoning enhances Formal Theorem Proving. ICML Ruida Wang, Rui Pan, Yuxin Li, Jipeng Zhang, Yizhen Jia, Shizhe Diao, Renjie Pi, Junjie Hu, Tong Zhang
2025	J	`jnl`	MA-LoT: Multi-Agent Lean-based Long Chain-of-Thought Reasoning enhances Formal Theorem Proving. CoRR Ruida Wang, Rui Pan, Yuxin Li, Jipeng Zhang, Yizhen Jia, Shizhe Diao, Renjie Pi, Junjie Hu, Tong Zhang
2025	J	`jnl`	MergeBench: A Benchmark for Merging Domain-Specialized LLMs. CoRR Yifei He, Siqi Zeng, Yuzheng Hu, Rui Yang, Tong Zhang, Han Zhao
2025	A*	`conf`	MiCRo: Mixture Modeling and Context-aware Routing for Personalized Preference Learning. EMNLP Jingyan Shen, Jiarui Yao, Rui Yang, Yifan Sun, Feng Luo, Rui Pan, Tong Zhang, Han Zhao
2025	J	`jnl`	MiCRo: Mixture Modeling and Context-aware Routing for Personalized Preference Learning. CoRR Jingyan Shen, Jiarui Yao, Rui Yang, Yifan Sun, Feng Luo, Rui Pan, Tong Zhang, Han Zhao
2025	J	`jnl`	Motion-Aware Concept Alignment for Consistent Video Editing. CoRR Tong Zhang, Juan Carlos León Alcázar, Bernard Ghanem
2025	J	`jnl`	Multi-Step Consistency Models: Fast Generation with Theoretical Guarantees. CoRR Nishant Jain, Xunpeng Huang, Yian Ma, Tong Zhang
2025	J	`jnl`	Nearly Optimal Sample Complexity of Offline KL-Regularized Contextual Bandits under Single-Policy Concentrability. CoRR Qingyue Zhao, Kaixuan Ji, Heyang Zhao, Tong Zhang, Quanquan Gu
2025	J	`jnl`	On the Complexity Theory of Masked Discrete Diffusion: From poly(1/ε) to Nearly ε-Free. CoRR Xunpeng Huang, Yingyu Lin, Nishant Jain, Kaibo Wang, Difan Zou, Yian Ma, Tong Zhang
2025	J	`jnl`	Optimal Sample Selection Through Uncertainty Estimation and Its Application in Deep Learning. J. Mach. Learn. Res. Yong Lin, Chen Liu, Chenlu Ye, Qing Lian, Yuan Yao, Tong Zhang
2025	J	`jnl`	Optimizing Chain-of-Thought Reasoners via Gradient Variance Minimization in Rejection Sampling and RL. CoRR Jiarui Yao, Yifan Hao, Hanning Zhang, Hanze Dong, Wei Xiong, Nan Jiang, Tong Zhang
2025	A*	`conf`	Personalized Visual Instruction Tuning. ICLR Renjie Pi, Jianshu Zhang, Tianyang Han, Jipeng Zhang, Rui Pan, Tong Zhang
2025	J	`jnl`	RAG-RL: Advancing Retrieval-Augmented Generation via RL and Curriculum Learning. CoRR Jerry Huang, Siddarth Madala, Risham Sidhu, Cheng Niu, Julia Hockenmaier, Tong Zhang
2025	J	`jnl`	RAG-Reward: Optimizing RAG with Reward Modeling and RLHF. CoRR Hanning Zhang, Juntong Song, Juno Zhu, Yuanhao Wu, Tong Zhang, Cheng Niu
2025	J	`jnl`	RM-R1: Reward Modeling as Reasoning. CoRR Xiusi Chen, Gaotang Li, Ziqi Wang, Bowen Jin, Cheng Qian, Yu Wang, Hongru Wang, Yu Zhang, Denghui Zhang, Tong Zhang, Hanghang Tong, Heng Ji
2025	J	`jnl`	ROCM: RLHF on consistency models. CoRR Shivanshu Shekhar, Tong Zhang
2025	J	`jnl`	Reinforce-Ada: An Adaptive Sampling Framework for Reinforce-Style LLM Training. CoRR Wei Xiong, Chenlu Ye, Baohao Liao, Hanze Dong, Xinxing Xu, Christof Monz, Jiang Bian, Nan Jiang, Tong Zhang
2025	J	`jnl`	Reverse Markov Learning: Multi-Step Generative Models for Complex Distributions. CoRR Xinwei Shen, Nicolai Meinshausen, Tong Zhang
2025	J	`jnl`	SEE-DPO: Self Entropy Enhanced Direct Preference Optimization. Trans. Mach. Learn. Res. Shivanshu Shekhar, Shreyas Singh, Tong Zhang
2025	—	`conf`	ScaleBiO: Scalable Bilevel Optimization for LLM Data Reweighting. ACL (1) Rui Pan, Dylan Zhang, Hanning Zhang, Xingyuan Pan, Minrui Xu, Jipeng Zhang, Renjie Pi, Xiaoyu Wang, Tong Zhang
2025	J	`jnl`	Self-rewarding correction for mathematical reasoning. CoRR Wei Xiong, Hanning Zhang, Chenlu Ye, Lichang Chen, Nan Jiang, Tong Zhang
2025	—	`conf`	TAGCOS: Task-agnostic Gradient Clustered Coreset Selection for Instruction Tuning Data. NAACL (Findings) Jipeng Zhang, Yaxuan Qin, Renjie Pi, Weizhong Zhang, Rui Pan, Tong Zhang
2025	J	`jnl`	The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS). CoRR Andrew Ferguson, Marisa Lafleur, Lars Ruthotto, Jesse Thaler, Yuan-Sen Ting, Pratyush Tiwary, Soledad Villar, E. Paulo Alves, Jeremy Avigad, Simon Billinge, Camille L. Bilodeau, Keith Brown, Emmanuel J. Candès, Arghya Chattopadhyay, Bingqing Cheng, Jonathan Clausen, Connor W. Coley, Andrew J. Connolly, Fred Daum, Sijia S. Dong, Chrisy Xiyu Du, Cora Dvorkin, Cristiano Fanelli, Eric B. Ford, Luis Manuel Frutos, Nicolás García Trillos, Cecilia Garraffo, Robert Ghrist, Rafael Gómez-Bombarelli, Gianluca Guadagni, Sreelekha Guggilam, Sergei Gukov, Juan B. Gutierrez, Salman Habib, Johannes Hachmann, Boris Hanin, Philip C. Harris, Murray Holland, Elizabeth Holm, Hsin-Yuan Huang, Shih-Chieh Hsu, Nick Jackson, Olexandr Isayev, Heng Ji, Aggelos K. Katsaggelos, Jeremy Kepner, Yannis G. Kevrekidis, Michelle P. Kuchera, J. Nathan Kutz, Branislava Lalic, Ann Lee, Matt LeBlanc, Josiah Lim, Rebecca Lindsey, Yongmin Liu, Peter Y. Lu, Sudhir Malik, Vuk Mandic, Vidya B. Manian, Emeka P. Mazi, Pankaj Mehta, Peter Melchior, Brice Ménard, Jennifer Ngadiuba, Stella Offner, Elsa Olivetti, Shyue Ping Ong, Christopher Rackauckas, Philippe Rigollet, Chad Risko, Philip Romero, Grant M. Rotskoff, Brett Savoie, Uros Seljak, David Shih, Gary Shiu, Dima Shlyakhtenko, Eva Silverstein, Taylor Sparks, Thomas Strohmer, Christopher Stubbs, Stephen Thomas, Suriyanarayanan Vaikuntanathan, René Vidal, Francisco Villaescusa-Navarro, Gregory Voth, Benjamin Wandelt, Rachel Ward, Melanie Weber, Risa Wechsler, Stephen Whitelam, Olaf Wiest, Mike Williams, Zhuoran Yang, Yaroslava G. Yingling, Bin Yu, Shuwen Yue, Ann Zabludoff, Huimin Zhao, Tong Zhang
2025	J	`jnl`	Theoretical Analysis on how Learning Rate Warmup Accelerates Convergence. CoRR Yuxing Liu, Yuze Ge, Rui Pan, An Kang, Tong Zhang
2025	J	`jnl`	Thinking vs. Doing: Agents that Reason by Scaling Test-Time Interaction. CoRR Junhong Shen, Hao Bai, Lunjun Zhang, Yifei Zhou, Amrith Setlur, Shengbang Tong, Diego Caples, Nan Jiang, Tong Zhang, Ameet Talwalkar, Aviral Kumar
2025	J	`jnl`	Towards Better Generalization via Distributional Input Projection Network. CoRR Yifan Hao, Yanxin Lu, Xinwei Shen, Tong Zhang
2025	J	`jnl`	Transformers as Multi-task Learners: Decoupling Features in Hidden Markov Models. CoRR Yifan Hao, Chenlu Ye, Chi Han, Tong Zhang
2025	J	`jnl`	Unbiased Gradient Low-Rank Projection. CoRR Rui Pan, Yang Luo, Yuxing Liu, Yang You, Tong Zhang
2025	A*	`conf`	Understanding Overadaptation in Supervised Fine-Tuning: The Role of Ensemble Methods. ICML Yifan Hao, Xingyuan Pan, Hanning Zhang, Chenlu Ye, Rui Pan, Tong Zhang
2025	J	`jnl`	Understanding Overadaptation in Supervised Fine-Tuning: The Role of Ensemble Methods. CoRR Yifan Hao, Xingyuan Pan, Hanning Zhang, Chenlu Ye, Rui Pan, Tong Zhang
2025	J	`jnl`	VL-GenRM: Enhancing Vision-Language Verification via Vision Experts and Iterative Training. CoRR Jipeng Zhang, Kehao Miao, Renjie Pi, Zhaowei Wang, Runtao Liu, Rui Pan, Tong Zhang
2024	A*	`conf`	A Sober Look at the Robustness of CLIPs to Spurious Features. NeurIPS Qizhou Wang, Yong Lin, Yongqiang Chen, Ludwig Schmidt, Bo Han, Tong Zhang
2024	J	`jnl`	A Theoretical Analysis of Nash Learning from Human Feedback under General KL-Regularized Preference. CoRR Chenlu Ye, Wei Xiong, Yuheng Zhang, Nan Jiang, Tong Zhang
2024	A*	`conf`	Accelerated Convergence of Stochastic Heavy Ball Method under Anisotropic Gradient Noise. ICLR Rui Pan, Yuxing Liu, Xiaoyu Wang, Tong Zhang
2024	—	`conf`	Active Prompting with Chain-of-Thought for Large Language Models. ACL (1) Shizhe Diao, Pengcheng Wang, Yong Lin, Rui Pan, Xiang Liu, Tong Zhang
2024	J	`jnl`	Alopex: A Computational Framework for Enabling On-Device Function Calls with LLMs. CoRR Yide Ran, Zhaozhuo Xu, Yuhang Yao, Zijian Hu, Shanshan Han, Han Jin, Alay Dilipbhai Shah, Jipeng Zhang, Dimitris Stripelis, Tong Zhang, Salman Avestimehr, Chaoyang He
2024	J	`jnl`	An Improved Analysis of Langevin Algorithms with Prior Diffusion for Non-Log-Concave Sampling. CoRR Xunpeng Huang, Hanze Dong, Difan Zou, Tong Zhang
2024	—	`conf`	An Incremental Unified Framework for Small Defect Inspection. ECCV (31) Jiaqi Tang, Hao Lu, Xiaogang Xu, Ruizheng Wu, Sixing Hu, Tong Zhang, Tsz Wa Cheng, Ming Ge, Ying-Cong Chen, Fugee Tsung
2024	—	`conf`	Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective Rewards. ACL (1) Haoxiang Wang, Yong Lin, Wei Xiong, Rui Yang, Shizhe Diao, Shuang Qiu, Han Zhao, Tong Zhang
2024	J	`jnl`	Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective Rewards. CoRR Haoxiang Wang, Yong Lin, Wei Xiong, Rui Yang, Shizhe Diao, Shuang Qiu, Han Zhao, Tong Zhang
2024	J	`jnl`	AstroLLaMA-Chat: Scaling AstroLLaMA with Conversational and Diverse Datasets. CoRR Ernest Perkowski, Rui Pan, Tuan Dung Nguyen, Yuan-Sen Ting, Sandor Kruk, Tong Zhang, Charlie O'Neill, Maja Jablonska, Zechang Sun, Michael J. Smith, Huiling Liu, Kevin Schawinski, Kartheik Iyer, Ioana Ciuca, UniverseTBD
2024	J	`jnl`	Bridge-Coder: Unlocking LLMs' Potential to Overcome Language Gaps in Low-Resource Code. CoRR Jipeng Zhang, Jianshu Zhang, Yuanzhe Li, Renjie Pi, Rui Pan, Runtao Liu, Ziqiang Zheng, Tong Zhang
2024	J	`jnl`	Building Math Agents with Multi-Turn Iterative Preference Learning. CoRR Wei Xiong, Chengshuai Shi, Jiaming Shen, Aviv Rosenberg, Zhen Qin, Daniele Calandriello, Misha Khalman, Rishabh Joshi, Bilal Piot, Mohammad Saleh, Chi Jin, Tong Zhang, Tianqi Liu
2024	J	`jnl`	Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithm. CoRR Miao Lu, Han Zhong, Tong Zhang, Jose H. Blanchet
2024	A*	`conf`	Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithms. NeurIPS Miao Lu, Han Zhong, Tong Zhang, Jose H. Blanchet
2024	J	`jnl`	Do CLIPs Always Generalize Better than ImageNet Models? CoRR Qizhou Wang, Yong Lin, Yongqiang Chen, Ludwig Schmidt, Bo Han, Tong Zhang
2024	—	`conf`	Enhancing Dialogue State Tracking Models through LLM-backed User-Agents Simulation. ACL (1) Cheng Niu, Xingguang Wang, Xuxin Cheng, Juntong Song, Tong Zhang
2024	J	`jnl`	Enhancing Dialogue State Tracking Models through LLM-backed User-Agents Simulation. CoRR Cheng Niu, Xingguang Wang, Xuxin Cheng, Juntong Song, Tong Zhang
2024	J	`jnl`	EntailE: Introducing Textual Entailment in Commonsense Knowledge Graph Completion. CoRR Ying Su, Tianqing Fang, Huiru Xiao, Weiqi Wang, Yangqiu Song, Tong Zhang, Lei Chen
2024	J	`jnl`	Entropy-Regularized Process Reward Model. CoRR Hanning Zhang, Pengcheng Wang, Shizhe Diao, Yong Lin, Rui Pan, Hanze Dong, Dylan Zhang, Pavlo Molchanov, Tong Zhang
2024	J	`jnl`	Fast Rates in Pool-Based Batch Active Learning. J. Mach. Learn. Res. Claudio Gentile, Zhilei Wang, Tong Zhang
2024	A*	`conf`	Faster Sampling via Stochastic Gradient Proximal Sampler. ICML Xunpeng Huang, Difan Zou, Hanze Dong, Yian Ma, Tong Zhang
2024	J	`jnl`	Faster Sampling via Stochastic Gradient Proximal Sampler. CoRR Xunpeng Huang, Difan Zou, Yi-An Ma, Hanze Dong, Tong Zhang
2024	A*	`conf`	Faster Sampling without Isoperimetry via Diffusion-based Monte Carlo. COLT Xunpeng Huang, Difan Zou, Hanze Dong, Yi-An Ma, Tong Zhang
2024	J	`jnl`	Faster Sampling without Isoperimetry via Diffusion-based Monte Carlo. CoRR Xunpeng Huang, Difan Zou, Hanze Dong, Yian Ma, Tong Zhang
2024	J	`jnl`	Fox-1 Technical Report. CoRR Zijian Hu, Jipeng Zhang, Rui Pan, Zhaozhuo Xu, Shanshan Han, Han Jin, Alay Dilipbhai Shah, Dimitris Stripelis, Yuhang Yao, Salman Avestimehr, Chaoyang He, Tong Zhang
2024	J	`jnl`	From Lists to Emojis: How Format Bias Affects Model Alignment. CoRR Xuanchang Zhang, Wei Xiong, Lichang Chen, Tianyi Zhou, Heng Huang, Tong Zhang
2024	J	`jnl`	Fully First-Order Methods for Decentralized Bilevel Optimization. CoRR Xiaoyu Wang, Xuxing Chen, Shiqian Ma, Tong Zhang
2024	J	`jnl`	Image Textualization: An Automatic Framework for Creating Accurate and Detailed Image Descriptions. CoRR Renjie Pi, Jianshu Zhang, Jipeng Zhang, Rui Pan, Zhekai Chen, Tong Zhang
2024	A*	`conf`	Image Textualization: An Automatic Framework for Generating Rich and Detailed Image Descriptions. NeurIPS Renjie Pi, Jianshu Zhang, Jipeng Zhang, Rui Pan, Zhekai Chen, Tong Zhang
2024	—	`conf`	Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts. EMNLP (Findings) Haoxiang Wang, Wei Xiong, Tengyang Xie, Han Zhao, Tong Zhang
2024	J	`jnl`	Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts. CoRR Haoxiang Wang, Wei Xiong, Tengyang Xie, Han Zhao, Tong Zhang
2024	A*	`conf`	Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-constraint. ICML Wei Xiong, Hanze Dong, Chenlu Ye, Ziqi Wang, Han Zhong, Heng Ji, Nan Jiang, Tong Zhang
2024	A*	`conf`	LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning. NeurIPS Rui Pan, Xiang Liu, Shizhe Diao, Renjie Pi, Jipeng Zhang, Chi Han, Tong Zhang
2024	J	`jnl`	LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning. CoRR Rui Pan, Xiang Liu, Shizhe Diao, Renjie Pi, Jipeng Zhang, Chi Han, Tong Zhang
2024	—	`conf`	LMFlow: An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. NAACL (Demonstrations) Shizhe Diao, Rui Pan, Hanze Dong, Kashun Shum, Jipeng Zhang, Wei Xiong, Tong Zhang
2024	J	`jnl`	Large Batch Analysis for Adagrad Under Anisotropic Smoothness. CoRR Yuxing Liu, Rui Pan, Tong Zhang
2024	J	`jnl`	Localize-and-Stitch: Efficient Model Merging via Sparse Task Arithmetic. CoRR Yifei He, Yuzheng Hu, Yong Lin, Tong Zhang, Han Zhao
2024	A*	`conf`	MEDL-U: Uncertainty-aware 3D Automatic Annotation based on Evidential Deep Learning. ICRA Helbert Paat, Qing Lian, Weilong Yao, Tong Zhang
2024	A*	`conf`	MLLM-Protector: Ensuring MLLM's Safety without Hurting Performance. EMNLP Renjie Pi, Tianyang Han, Jianshu Zhang, Yueqi Xie, Rui Pan, Qing Lian, Hanze Dong, Jipeng Zhang, Tong Zhang
2024	J	`jnl`	MLLM-Protector: Ensuring MLLM's Safety without Hurting Performance. CoRR Renjie Pi, Tianyang Han, Yueqi Xie, Rui Pan, Qing Lian, Hanze Dong, Jipeng Zhang, Tong Zhang
2024	J	`jnl`	MatchDiffusion: Training-free Generation of Match-cuts. CoRR Alejandro Pardo, Fabio Pizzati, Tong Zhang, Alexander Pondaven, Philip Torr, Juan Camilo Pérez, Bernard Ghanem
2024	A*	`conf`	Mitigating the Alignment Tax of RLHF. EMNLP Yong Lin, Hangyu Lin, Wei Xiong, Shizhe Diao, Jianmeng Liu, Jipeng Zhang, Rui Pan, Haoxiang Wang, Wenbin Hu, Hanning Zhang, Hanze Dong, Renjie Pi, Han Zhao, Nan Jiang, Heng Ji, Yuan Yao, Tong Zhang
2024	J	`jnl`	Nonsmooth Optimization over the Stiefel Manifold and Beyond: Proximal Gradient Method and Recent Variants. SIAM Rev. Shixiang Chen, Shiqian Ma, Anthony Man-Cho So, Tong Zhang
2024	J	`jnl`	On the Benefits of Over-parameterization for Out-of-Distribution Generalization. CoRR Yifan Hao, Yong Lin, Difan Zou, Tong Zhang
2024	—	`conf`	On the Limited Generalization Capability of the Implicit Reward Model Induced by Direct Preference Optimization. EMNLP (Findings) Yong Lin, Skyler Seto, Maartje ter Hoeve, Katherine Metcalf, Barry-John Theobald, Xuan Wang, Yizhe Zhang, Chen Huang, Tong Zhang
2024	J	`jnl`	On the Limited Generalization Capability of the Implicit Reward Model Induced by Direct Preference Optimization. CoRR Yong Lin, Skyler Seto, Maartje ter Hoeve, Katherine Metcalf, Barry-John Theobald, Xuan Wang, Yizhe Zhang, Chen Huang, Tong Zhang
2024	J	`jnl`	On the Unreasonable Effectiveness of Federated Averaging with Heterogeneous Data. Trans. Mach. Learn. Res. Jianyu Wang, Rudrajit Das, Gauri Joshi, Satyen Kale, Zheng Xu, Tong Zhang
2024	A*	`conf`	Online Iterative Reinforcement Learning from Human Feedback with General Preference Model. NeurIPS Chenlu Ye, Wei Xiong, Yuheng Zhang, Hanze Dong, Nan Jiang, Tong Zhang
2024	J	`jnl`	PAPAL: A Provable PArticle-based Primal-Dual ALgorithm for Mixed Nash Equilibrium. J. Mach. Learn. Res. Shihong Ding, Hanze Dong, Cong Fang, Zhouchen Lin, Tong Zhang
2024	A*	`conf`	PerceptionGPT: Effectively Fusing Visual Perception Into LLM. CVPR Renjie Pi, Lewei Yao, Jiahui Gao, Jipeng Zhang, Tong Zhang
2024	J	`jnl`	Personalized Visual Instruction Tuning. CoRR Renjie Pi, Jianshu Zhang, Tianyang Han, Jipeng Zhang, Rui Pan, Tong Zhang
2024	A*	`conf`	Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning. ICML Dake Zhang, Boxiang Lyu, Shuang Qiu, Mladen Kolar, Tong Zhang
2024	J	`jnl`	Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning. CoRR Dake Zhang, Boxiang Lyu, Shuang Qiu, Mladen Kolar, Tong Zhang
2024	—	`conf`	PipeNet: Question Answering with Semantic Pruning over Knowledge Graphs. *SEM@NAACL Ying Su, Jipeng Zhang, Yangqiu Song, Tong Zhang
2024	J	`jnl`	PipeNet: Question Answering with Semantic Pruning over Knowledge Graphs. CoRR Ying Su, Jipeng Zhang, Yangqiu Song, Tong Zhang
2024	—	`conf`	Plum: Prompt Learning using Metaheuristics. ACL (Findings) Rui Pan, Shuo Xing, Shizhe Diao, Wenhe Sun, Xiang Liu, Kashun Shum, Jipeng Zhang, Renjie Pi, Tong Zhang
2024	—	`conf`	R-Tuning: Instructing Large Language Models to Say 'I Don't Know'. NAACL-HLT Hanning Zhang, Shizhe Diao, Yong Lin, Yi R. Fung, Qing Lian, Xingyao Wang, Yangyi Chen, Heng Ji, Tong Zhang
2024	—	`conf`	RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Models. ACL (1) Cheng Niu, Yuanhao Wu, Juno Zhu, Siliang Xu, Kashun Shum, Randy Zhong, Juntong Song, Tong Zhang
2024	J	`jnl`	RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Models. CoRR Yuanhao Wu, Juno Zhu, Siliang Xu, Kashun Shum, Cheng Niu, Randy Zhong, Juntong Song, Tong Zhang
2024	J	`jnl`	RLHF Workflow: From Reward Modeling to Online RLHF. CoRR Hanze Dong, Wei Xiong, Bo Pang, Haoxiang Wang, Han Zhao, Yingbo Zhou, Nan Jiang, Doyen Sahoo, Caiming Xiong, Tong Zhang
2024	J	`jnl`	RLHF Workflow: From Reward Modeling to Online RLHF. Trans. Mach. Learn. Res. Hanze Dong, Wei Xiong, Bo Pang, Haoxiang Wang, Han Zhao, Yingbo Zhou, Nan Jiang, Doyen Sahoo, Caiming Xiong, Tong Zhang
2024	A*	`conf`	Regularizing Hidden States Enables Learning Generalizable Reward Model for LLMs. NeurIPS Rui Yang, Ruomeng Ding, Yong Lin, Huan Zhang, Tong Zhang
2024	J	`jnl`	Regularizing Hidden States Enables Learning Generalizable Reward Model for LLMs. CoRR Rui Yang, Ruomeng Ding, Yong Lin, Huan Zhang, Tong Zhang
2024	A*	`conf`	Reverse Diffusion Monte Carlo. ICLR Xunpeng Huang, Hanze Dong, Yifan Hao, Yian Ma, Tong Zhang
2024	A*	`conf`	Reverse Transition Kernel: A Flexible Framework to Accelerate Diffusion Inference. NeurIPS Xunpeng Huang, Difan Zou, Hanze Dong, Yi Zhang, Yian Ma, Tong Zhang
2024	J	`jnl`	Reverse Transition Kernel: A Flexible Framework to Accelerate Diffusion Inference. CoRR Xunpeng Huang, Difan Zou, Hanze Dong, Yi Zhang, Yi-An Ma, Tong Zhang
2024	J	`jnl`	SEE-DPO: Self Entropy Enhanced Direct Preference Optimization. CoRR Shivanshu Shekhar, Shreyas Singh, Tong Zhang
2024	J	`jnl`	ScaleBiO: Scalable Bilevel Optimization for LLM Data Reweighting. CoRR Rui Pan, Jipeng Zhang, Xingyuan Pan, Renjie Pi, Xiaoyu Wang, Tong Zhang
2024	J	`jnl`	Sharp Analysis for KL-Regularized Contextual Bandits and RLHF. CoRR Heyang Zhao, Chenlu Ye, Quanquan Gu, Tong Zhang
2024	J	`jnl`	Short-Term Load Forecasting Using Regularized Greedy Forest-Based Ensemble Model. IEEE Access Binnie Wai-Keung Yiu, Tong Zhang, Cheuk-Wing Lee
2024	A*	`conf`	Spurious Feature Diversification Improves Out-of-distribution Generalization. ICLR Yong Lin, Lu Tan, Yifan Hao, Honam Wong, Hanze Dong, Weizhong Zhang, Yujiu Yang, Tong Zhang
2024	—	`conf`	Strengthening Multimodal Large Language Model with Bootstrapped Preference Optimization. ECCV (33) Renjie Pi, Tianyang Han, Wei Xiong, Jipeng Zhang, Runtao Liu, Rui Pan, Tong Zhang
2024	J	`jnl`	Strengthening Multimodal Large Language Model with Bootstrapped Preference Optimization. CoRR Renjie Pi, Tianyang Han, Wei Xiong, Jipeng Zhang, Runtao Liu, Rui Pan, Tong Zhang
2024	J	`jnl`	TAGCOS: Task-agnostic Gradient Clustered Coreset Selection for Instruction Tuning Data. CoRR Jipeng Zhang, Yaxuan Qin, Renjie Pi, Weizhong Zhang, Rui Pan, Tong Zhang
2024	—	`conf`	TensorOpera Router: A Multi-Model Router for Efficient LLM Inference. EMNLP (Industry Track) Dimitris Stripelis, Zhaozhuo Xu, Zijian Hu, Alay Dilipbhai Shah, Han Jin, Yuhang Yao, Jipeng Zhang, Tong Zhang, Salman Avestimehr, Chaoyang He
2024	J	`jnl`	The Instinctive Bias: Spurious Images lead to Hallucination in MLLMs. CoRR Tianyang Han, Qing Lian, Rui Pan, Renjie Pi, Jipeng Zhang, Shizhe Diao, Yong Lin, Tong Zhang
2024	A*	`conf`	The Instinctive Bias: Spurious Images lead to Illusion in MLLMs. EMNLP Tianyang Han, Qing Lian, Rui Pan, Renjie Pi, Jipeng Zhang, Shizhe Diao, Yong Lin, Tong Zhang
2024	A*	`conf`	The Non-linear F-Design and Applications to Interactive Learning. ICML Alekh Agarwal, Jian Qian, Alexander Rakhlin, Tong Zhang
2024	J	`jnl`	The Surprising Harmfulness of Benign Overfitting for Adversarial Robustness. CoRR Yifan Hao, Tong Zhang
2024	A*	`conf`	TheoremLlama: Transforming General-Purpose LLMs into Lean4 Experts. EMNLP Ruida Wang, Jipeng Zhang, Yizhen Jia, Rui Pan, Shizhe Diao, Renjie Pi, Tong Zhang
2024	J	`jnl`	TheoremLlama: Transforming General-Purpose LLMs into Lean4 Experts. CoRR Ruida Wang, Jipeng Zhang, Yizhen Jia, Rui Pan, Shizhe Diao, Renjie Pi, Tong Zhang
2024	—	`conf`	Towards Better Generalization in Open-Domain Question Answering by Mitigating Context Memorization. NAACL-HLT (Findings) Zixuan Zhang, Revanth Gangi Reddy, Kevin Small, Tong Zhang, Heng Ji
2024	J	`jnl`	Towards Better Generalization in Open-Domain Question Answering by Mitigating Context Memorization. CoRR Zixuan Zhang, Revanth Gangi Reddy, Kevin Small, Tong Zhang, Heng Ji
2024	A*	`conf`	Towards Robust Model-Based Reinforcement Learning Against Adversarial Corruption. ICML Chenlu Ye, Jiafan He, Quanquan Gu, Tong Zhang
2024	J	`jnl`	Towards Robust Model-Based Reinforcement Learning Against Adversarial Corruption. CoRR Chenlu Ye, Jiafan He, Quanquan Gu, Tong Zhang
2024	A*	`conf`	Towards Robust Offline Reinforcement Learning under Diverse Data Corruption. ICLR Rui Yang, Han Zhong, Jiawei Xu, Amy Zhang, Chongjie Zhang, Lei Han, Tong Zhang
2024	J	`jnl`	Traversing Pareto Optimal Policies: Provably Efficient Multi-Objective Reinforcement Learning. CoRR Shuang Qiu, Dake Zhang, Rui Yang, Boxiang Lyu, Tong Zhang
2024	—	`conf`	VeraCT Scan: Retrieval-Augmented Fake News Detection with Justifiable Reasoning. ACL (3) Cheng Niu, Yang Guan, Yuanhao Wu, Juno Zhu, Juntong Song, Randy Zhong, Kaihua Zhu, Siliang Xu, Shizhe Diao, Tong Zhang
2024	J	`jnl`	VeraCT Scan: Retrieval-Augmented Fake News Detection with Justifiable Reasoning. CoRR Cheng Niu, Yang Guan, Yuanhao Wu, Juno Zhu, Juntong Song, Randy Zhong, Kaihua Zhu, Siliang Xu, Shizhe Diao, Tong Zhang
2023	A*	`conf`	A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes. NeurIPS Han Zhong, Tong Zhang
2023	J	`jnl`	A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes. CoRR Han Zhong, Tong Zhang
2023	J	`jnl`	Accelerated Convergence of Stochastic Heavy Ball Method under Anisotropic Gradient Noise. CoRR Rui Pan, Yuxing Liu, Xiaoyu Wang, Tong Zhang
2023	J	`jnl`	Active Prompting with Chain-of-Thought for Large Language Models. CoRR Shizhe Diao, Pengcheng Wang, Yong Lin, Tong Zhang
2023	J	`jnl`	An Incremental Unified Framework for Small Defect Inspection. CoRR Jiaqi Tang, Hao Lu, Xiaogang Xu, Ruizheng Wu, Sixing Hu, Tong Zhang, Tsz Wa Cheng, Ming Ge, Ying-Cong Chen, Fugee Tsung
2023	—	`conf`	Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled Data. EMNLP (Findings) Kashun Shum, Shizhe Diao, Tong Zhang
2023	J	`jnl`	Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled Data. CoRR Kashun Shum, Shizhe Diao, Tong Zhang
2023	A*	`conf`	Beyond Uniform Lipschitz Condition in Differentially Private Optimization. ICML Rudrajit Das, Satyen Kale, Zheng Xu, Tong Zhang, Sujay Sanghavi
2023	J	`jnl`	Black-Box Prompt Learning for Pre-trained Language Models. Trans. Mach. Learn. Res. Shizhe Diao, Zhichao Huang, Ruijia Xu, Xuechun Li, Yong Lin, Xiao Zhou, Tong Zhang
2023	A	`conf`	Catalyst Acceleration of Error Compensated Methods Leads to Better Communication Complexity. AISTATS Xun Qian, Hanze Dong, Tong Zhang, Peter Richtárik
2023	J	`jnl`	Compressive Spectral Imaging via Misalignment Induced Equivalent Grayscale Coded Aperture. IEEE Geosci. Remote. Sens. Lett. Tong Zhang, Shengjie Zhao, Xu Ma, Andres Ramirez-Jaime, Qile Zhao, Gonzalo R. Arce
2023	A*	`conf`	Corruption-Robust Algorithms with Uncertainty Weighting for Nonlinear Contextual Bandits and Markov Decision Processes. ICML Chenlu Ye, Wei Xiong, Quanquan Gu, Tong Zhang
2023	A*	`conf`	Corruption-Robust Offline Reinforcement Learning with General Function Approximation. NeurIPS Chenlu Ye, Rui Yang, Quanquan Gu, Tong Zhang
2023	J	`jnl`	Corruption-Robust Offline Reinforcement Learning with General Function Approximation. CoRR Chenlu Ye, Rui Yang, Quanquan Gu, Tong Zhang
2023	A*	`conf`	Covariate-Shift Generalization via Random Sample Weighting. AAAI Yue He, Xinwei Shen, Renzhe Xu, Tong Zhang, Yong Jiang, Wenchao Zou, Peng Cui
2023	A*	`conf`	DetGPT: Detect What You Need via Reasoning. EMNLP Renjie Pi, Jiahui Gao, Shizhe Diao, Rui Pan, Hanze Dong, Jipeng Zhang, Lewei Yao, Jianhua Han, Hang Xu, Lingpeng Kong, Tong Zhang
2023	J	`jnl`	DetGPT: Detect What You Need via Reasoning. CoRR Renjie Pi, Jiahui Gao, Shizhe Diao, Rui Pan, Hanze Dong, Jipeng Zhang, Lewei Yao, Jianhua Han, Hang Xu, Lingpeng Kong, Tong Zhang
2023	A*	`conf`	Doolittle: Benchmarks and Corpora for Academic Writing Formalization. EMNLP Shizhe Diao, Yongyu Lei, Liangming Pan, Tianqing Fang, Wangchunshu Zhou, Sedrick Scott Keh, Min-Yen Kan, Tong Zhang
2023	A*	`conf`	Double Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coverage. NeurIPS Jose H. Blanchet, Miao Lu, Tong Zhang, Han Zhong
2023	J	`jnl`	Double Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coverage. CoRR Jose H. Blanchet, Miao Lu, Tong Zhang, Han Zhong
2023	A*	`conf`	Double Randomized Underdamped Langevin with Dimension-Independent Convergence Guarantee. NeurIPS Yuanshi Liu, Cong Fang, Tong Zhang
2023	J	`jnl`	Environment Invariant Linear Least Squares. CoRR Jianqing Fan, Cong Fang, Yihong Gu, Tong Zhang
2023	A*	`conf`	Generalized Polyak Step Size for First Order Optimization with Momentum. ICML Xiaoyu Wang, Mikael Johansson, Tong Zhang
2023	J	`jnl`	Gibbs Sampling from Human Feedback: A Provable KL- constrained Framework for RLHF. CoRR Wei Xiong, Hanze Dong, Chenlu Ye, Han Zhong, Nan Jiang, Tong Zhang
2023	A*	`conf`	Hashtag-Guided Low-Resource Tweet Classification. WWW Shizhe Diao, Sedrick Scott Keh, Liangming Pan, Zhiliang Tian, Yan Song, Tong Zhang
2023	J	`jnl`	Hashtag-Guided Low-Resource Tweet Classification. CoRR Shizhe Diao, Sedrick Scott Keh, Liangming Pan, Zhiliang Tian, Yan Song, Tong Zhang
2023	A*	`conf`	Inconsistency, Instability, and Generalization Gap of Deep Neural Network Training. NeurIPS Rie Johnson, Tong Zhang
2023	J	`jnl`	Inconsistency, Instability, and Generalization Gap of Deep Neural Network Training. CoRR Rie Johnson, Tong Zhang
2023	J	`jnl`	LMFlow: An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. CoRR Shizhe Diao, Rui Pan, Hanze Dong, Kashun Shum, Jipeng Zhang, Wei Xiong, Tong Zhang
2023	A*	`conf`	Learning in POMDPs is Sample-Efficient with Hindsight Observability. ICML Jonathan Lee, Alekh Agarwal, Christoph Dann, Tong Zhang
2023	J	`jnl`	Learning in POMDPs is Sample-Efficient with Hindsight Observability. CoRR Jonathan N. Lee, Alekh Agarwal, Christoph Dann, Tong Zhang
2023	J	`jnl`	MEDL-U: Uncertainty-aware 3D Automatic Annotator based on Evidential Deep Learning. CoRR Helbert Paat, Qing Lian, Weilong Yao, Tong Zhang
2023	J	`jnl`	Mitigating the Alignment Tax of RLHF. CoRR Yong Lin, Hangyu Lin, Wei Xiong, Shizhe Diao, Jianmeng Liu, Jipeng Zhang, Rui Pan, Haoxiang Wang, Wenbin Hu, Hanning Zhang, Hanze Dong, Renjie Pi, Han Zhao, Nan Jiang, Yuan Yao, Tong Zhang
2023	J	`jnl`	Mixture-of-Domain-Adapters: Decoupling and Injecting Domain Knowledge to Pre-trained Language Models Memories. CoRR Shizhe Diao, Tianyang Xu, Ruijia Xu, Jiawei Wang, Tong Zhang
2023	—	`conf`	Mixture-of-Domain-Adapters: Decoupling and Injecting Domain Knowledge to Pre-trained Language Models' Memories. ACL (1) Shizhe Diao, Tianyang Xu, Ruijia Xu, Jiawei Wang, Tong Zhang
2023	J	`jnl`	Model Agnostic Sample Reweighting for Out-of-Distribution Learning. CoRR Xiao Zhou, Yong Lin, Renjie Pi, Weizhong Zhang, Renzhe Xu, Peng Cui, Tong Zhang
2023	J	`jnl`	Monte Carlo Sampling without Isoperimetry: A Reverse Diffusion Approach. CoRR Xunpeng Huang, Hanze Dong, Yifan Hao, Yian Ma, Tong Zhang
2023	J	`jnl`	Multi-Consensus Decentralized Accelerated Gradient Descent. J. Mach. Learn. Res. Haishan Ye, Luo Luo, Ziang Zhou, Tong Zhang
2023	A*	`conf`	Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game. ICLR Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Liwei Wang, Tong Zhang
2023	A*	`conf`	On the Convergence of Federated Averaging with Cyclic Client Participation. ICML Yae Jee Cho, Pranay Sharma, Gauri Joshi, Zheng Xu, Satyen Kale, Tong Zhang
2023	J	`jnl`	On the Convergence of Federated Averaging with Cyclic Client Participation. CoRR Yae Jee Cho, Pranay Sharma, Gauri Joshi, Zheng Xu, Satyen Kale, Tong Zhang
2023	J	`jnl`	Optimal Sample Selection Through Uncertainty Estimation and Its Application in Deep Learning. CoRR Yong Lin, Chen Liu, Chenlu Ye, Qing Lian, Yuan Yao, Tong Zhang
2023	A*	`conf`	Particle-based Variational Inference with Preconditioned Functional Gradient Flow. ICLR Hanze Dong, Xi Wang, Yong Lin, Tong Zhang
2023	J	`jnl`	PerceptionGPT: Effectively Fusing Visual Perception into LLM. CoRR Renjie Pi, Lewei Yao, Jiahui Gao, Jipeng Zhang, Tong Zhang
2023	J	`jnl`	Plum: Prompt Learning using Metaheuristic. CoRR Rui Pan, Shuo Xing, Shizhe Diao, Xiang Liu, Kashun Shum, Jipeng Zhang, Tong Zhang
2023	A*	`conf`	Posterior Sampling for Competitive RL: Function Approximation and Partial Observation. NeurIPS Shuang Qiu, Ziyu Dai, Han Zhong, Zhaoran Wang, Zhuoran Yang, Tong Zhang
2023	J	`jnl`	Posterior Sampling for Competitive RL: Function Approximation and Partial Observation. CoRR Shuang Qiu, Ziyu Dai, Han Zhong, Zhaoran Wang, Zhuoran Yang, Tong Zhang
2023	J	`jnl`	Probabilistic Bilevel Coreset Selection. CoRR Xiao Zhou, Renjie Pi, Weizhong Zhang, Yong Lin, Tong Zhang
2023	J	`jnl`	Provable Particle-based Primal-Dual Algorithm for Mixed Nash Equilibrium. CoRR Shihong Ding, Hanze Dong, Cong Fang, Zhouchen Lin, Tong Zhang
2023	J	`jnl`	R-Tuning: Teaching Large Language Models to Refuse Unknown Questions. CoRR Hanning Zhang, Shizhe Diao, Yong Lin, Yi R. Fung, Qing Lian, Xingyao Wang, Yangyi Chen, Heng Ji, Tong Zhang
2023	J	`jnl`	RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment. CoRR Hanze Dong, Wei Xiong, Deepanshu Goyal, Rui Pan, Shizhe Diao, Jipeng Zhang, Kashun Shum, Tong Zhang
2023	J	`jnl`	RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment. Trans. Mach. Learn. Res. Hanze Dong, Wei Xiong, Deepanshu Goyal, Yihan Zhang, Winnie Chow, Rui Pan, Shizhe Diao, Jipeng Zhang, Kashun Shum, Tong Zhang
2023	J	`jnl`	Spurious Feature Diversification Improves Out-of-distribution Generalization. CoRR Yong Lin, Lu Tan, Yifan Hao, Honam Wong, Hanze Dong, Weizhong Zhang, Yujiu Yang, Tong Zhang
2023	J	`jnl`	Towards Robust Offline Reinforcement Learning under Diverse Data Corruption. CoRR Rui Yang, Han Zhong, Jiawei Xu, Amy Zhang, Chongjie Zhang, Lei Han, Tong Zhang
2023	A*	`conf`	VOQL: Towards Optimal Regret in Model-free RL with Nonlinear Function Approximation. COLT Alekh Agarwal, Yujia Jin, Tong Zhang
2023	A*	`conf`	Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency. COLT Heyang Zhao, Jiafan He, Dongruo Zhou, Tong Zhang, Quanquan Gu
2023	J	`jnl`	Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency. CoRR Heyang Zhao, Jiafan He, Dongruo Zhou, Tong Zhang, Quanquan Gu
2023	A*	`conf`	What is Essential for Unseen Goal Generalization of Offline Goal-conditioned RL? ICML Rui Yang, Lin Yong, Xiaoteng Ma, Hao Hu, Chongjie Zhang, Tong Zhang
2023	J	`jnl`	What is Essential for Unseen Goal Generalization of Offline Goal-conditioned RL? CoRR Rui Yang, Yong Lin, Xiaoteng Ma, Hao Hu, Chongjie Zhang, Tong Zhang
2022	J	`jnl`	A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning. CoRR Christoph Dann, Mehryar Mohri, Tong Zhang, Julian Zimmert
2022	A*	`conf`	A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games. ICML Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Tong Zhang
2022	J	`jnl`	A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games. CoRR Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Tong Zhang
2022	A*	`conf`	A Theoretical Analysis on Independence-driven Importance Weighting for Covariate-shift Generalization. ICML Renzhe Xu, Xingxuan Zhang, Zheyan Shen, Tong Zhang, Peng Cui
2022	J	`jnl`	A stochastic extra-step quasi-Newton method for nonsmooth nonconvex optimization. Math. Program. Minghan Yang, Andre Milzarek, Zaiwen Wen, Tong Zhang
2022	A*	`conf`	Achieving Minimax Rates in Pool-Based Batch Active Learning. ICML Claudio Gentile, Zhilei Wang, Tong Zhang
2022	J	`jnl`	Achieving Minimax Rates in Pool-Based Batch Active Learning. CoRR Claudio Gentile, Zhilei Wang, Tong Zhang
2022	J	`jnl`	Asymptotic Statistical Analysis of f-divergence GAN. CoRR Xinwei Shen, Kani Chen, Tong Zhang
2022	A*	`conf`	Bayesian Invariant Risk Minimization. CVPR Yong Lin, Hanze Dong, Hao Wang, Tong Zhang
2022	A*	`conf`	Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint. ICML Hao Liu, Minshuo Chen, Siawpeng Er, Wenjing Liao, Tong Zhang, Tuo Zhao
2022	J	`jnl`	Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint. CoRR Hao Liu, Minshuo Chen, Siawpeng Er, Wenjing Liao, Tong Zhang, Tuo Zhao
2022	J	`jnl`	Beyond Uniform Lipschitz Condition in Differentially Private Optimization. CoRR Rudrajit Das, Satyen Kale, Zheng Xu, Tong Zhang, Sujay Sanghavi
2022	J	`jnl`	Black-box Prompt Learning for Pre-trained Language Models. CoRR Shizhe Diao, Xuechun Li, Yong Lin, Zhichao Huang, Tong Zhang
2022	J	`jnl`	Compressive Spectral X-Ray CT Reconstruction via Deep Learning. IEEE Trans. Computational Imaging Tong Zhang, Shengjie Zhao, Xu Ma, Carlos M. Restrepo, Gonzalo R. Arce
2022	J	`jnl`	Convex Formulation of Overparameterized Deep Neural Networks. IEEE Trans. Inf. Theory Cong Fang, Yihong Gu, Weizhong Zhang, Tong Zhang
2022	J	`jnl`	Corruption-Robust Algorithms with Uncertainty Weighting for Nonlinear Contextual Bandits and Markov Decision Processes. CoRR Chenlu Ye, Wei Xiong, Quanquan Gu, Tong Zhang
2022	J	`jnl`	Dimension Independent Generalization of DP-SGD for Overparameterized Smooth Convex Optimization. CoRR Yi-An Ma, Teodor Vanislavov Marinov, Tong Zhang
2022	A*	`conf`	Eigencurve: Optimal Learning Rate Schedule for SGD on Quadratic Objectives with Skewed Hessian Spectrums. ICLR Rui Pan, Haishan Ye, Tong Zhang
2022	J	`jnl`	Exploiting Hybrid Semantics of Relation Paths for Multi-hop Question Answering Over Knowledge Graphs. CoRR Zile Qiao, Wei Ye, Tong Zhang, Tong Mo, Weiping Li, Shikun Zhang
2022	B	`conf`	Exploiting Hybrid Semantics of Relation Paths for Multi-hop Question Answering over Knowledge Graphs. COLING Zile Qiao, Wei Ye, Tong Zhang, Tong Mo, Weiping Li, Shikun Zhang
2022	A*	`conf`	Exploring Geometric Consistency for Monocular 3D Object Detection. CVPR Qing Lian, Botao Ye, Ruijia Xu, Weilong Yao, Tong Zhang
2022	J	`jnl`	ExtremeBERT: A Toolkit for Accelerating Pretraining of Customized BERT. CoRR Rui Pan, Shizhe Diao, Jianlin Chen, Tong Zhang
2022	J	`jnl`	Feel-Good Thompson Sampling for Contextual Bandits and Reinforcement Learning. SIAM J. Math. Data Sci. Tong Zhang
2022	A*	`conf`	Frequency-Aware Contrastive Learning for Neural Machine Translation. AAAI Tong Zhang, Wei Ye, Baosong Yang, Long Zhang, Xingzhang Ren, Dayiheng Liu, Jinan Sun, Shikun Zhang, Haibo Zhang, Wen Zhao
2022	J	`jnl`	GEC: A Unified Framework for Interactive Decision Making in MDP, POMDP, and Beyond. CoRR Han Zhong, Wei Xiong, Sirui Zheng, Liwei Wang, Zhaoran Wang, Zhuoran Yang, Tong Zhang
2022	A*	`conf`	HyperDQN: A Randomized Exploration Method for Deep Reinforcement Learning. ICLR Ziniu Li, Yingru Li, Yushun Zhang, Tong Zhang, Zhi-Quan Luo
2022	—	`conf`	MICO: A Multi-alternative Contrastive Learning Framework for Commonsense Knowledge Representation. EMNLP (Findings) Ying Su, Zihao Wang, Tianqing Fang, Hongming Zhang, Yangqiu Song, Tong Zhang
2022	J	`jnl`	MICO: A Multi-alternative Contrastive Learning Framework for Commonsense Knowledge Representation. CoRR Ying Su, Zihao Wang, Tianqing Fang, Hongming Zhang, Yangqiu Song, Tong Zhang
2022	A*	`conf`	Minimax Regret Optimization for Robust Machine Learning under Distribution Shift. COLT Alekh Agarwal, Tong Zhang
2022	J	`jnl`	Minimax Regret Optimization for Robust Machine Learning under Distribution Shift. CoRR Alekh Agarwal, Tong Zhang
2022	A*	`conf`	Model Agnostic Sample Reweighting for Out-of-Distribution Learning. ICML Xiao Zhou, Yong Lin, Renjie Pi, Weizhong Zhang, Renzhe Xu, Peng Cui, Tong Zhang
2022	A*	`conf`	Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity. NeurIPS Alekh Agarwal, Tong Zhang
2022	J	`jnl`	Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity. CoRR Alekh Agarwal, Tong Zhang
2022	B	`conf`	Multilingual Word Sense Disambiguation with Unified Sense Representation. COLING Ying Su, Hongming Zhang, Yangqiu Song, Tong Zhang
2022	J	`jnl`	Multilingual Word Sense Disambiguation with Unified Sense Representation. CoRR Ying Su, Hongming Zhang, Yangqiu Song, Tong Zhang
2022	J	`jnl`	Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game. CoRR Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Liwei Wang, Tong Zhang
2022	A*	`conf`	Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions. NeurIPS Jiafan He, Dongruo Zhou, Tong Zhang, Quanquan Gu
2022	J	`jnl`	Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions. CoRR Jiafan He, Dongruo Zhou, Tong Zhang, Quanquan Gu
2022	A*	`conf`	Non-Linear Reinforcement Learning in Large Action Spaces: Structural Conditions and Sample-efficiency of Posterior Sampling. COLT Alekh Agarwal, Tong Zhang
2022	J	`jnl`	Non-Linear Reinforcement Learning in Large Action Spaces: Structural Conditions and Sample-efficiency of Posterior Sampling. CoRR Alekh Agarwal, Tong Zhang
2022	J	`jnl`	Normalizing Flow with Variational Latent Representation. CoRR Hanze Dong, Shizhe Diao, Weizhong Zhang, Tong Zhang
2022	J	`jnl`	On the Unreasonable Effectiveness of Federated Averaging with Heterogeneous Data. CoRR Jianyu Wang, Rudrajit Das, Gauri Joshi, Satyen Kale, Zheng Xu, Tong Zhang
2022	J	`jnl`	Particle-based Variational Inference with Preconditioned Functional Gradient Flow. CoRR Hanze Dong, Xi Wang, Yong Lin, Tong Zhang
2022	A*	`conf`	Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets. ICML Han Zhong, Wei Xiong, Jiyuan Tan, Liwei Wang, Tong Zhang, Zhaoran Wang, Zhuoran Yang
2022	J	`jnl`	Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets. CoRR Han Zhong, Wei Xiong, Jiyuan Tan, Liwei Wang, Tong Zhang, Zhaoran Wang, Zhuoran Yang
2022	A*	`conf`	Probabilistic Bilevel Coreset Selection. ICML Xiao Zhou, Renjie Pi, Weizhong Zhang, Yong Lin, Zonghao Chen, Tong Zhang
2022	—	`conf`	Rare and Zero-shot Word Sense Disambiguation using Z-Reweighting. ACL (1) Ying Su, Hongming Zhang, Yangqiu Song, Tong Zhang
2022	—	`conf`	Semi-supervised Monocular 3D Object Detection by Multi-view Consistency. ECCV (8) Qing Lian, Yanbo Xu, Weilong Yao, Yingcong Chen, Tong Zhang
2022	A*	`conf`	Sparse Invariant Risk Minimization. ICML Xiao Zhou, Yong Lin, Weizhong Zhang, Tong Zhang
2022	J	`jnl`	VOQL: Towards Optimal Regret in Model-free RL with Nonlinear Function Approximation. CoRR Alekh Agarwal, Yujia Jin, Tong Zhang
2022	J	`jnl`	Weakly Supervised Disentangled Generative Causal Representation Learning. J. Mach. Learn. Res. Xinwei Shen, Furui Liu, Hanze Dong, Qing Lian, Zhitang Chen, Tong Zhang
2022	J	`jnl`	When is the Convergence Time of Langevin Algorithms Dimension Independent? A Composite Optimization Viewpoint. J. Mach. Learn. Res. Yoav Freund, Yi-An Ma, Tong Zhang
2021	J	`jnl`	A Field Guide to Federated Optimization. CoRR Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Agüera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas N. Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horváth, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecný, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtárik, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake E. Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu
2021	J	`jnl`	A Framework of Composite Functional Gradient Methods for Generative Adversarial Models. IEEE Trans. Pattern Anal. Mach. Intell. Rie Johnson, Tong Zhang
2021	A*	`conf`	A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning. NeurIPS Christoph Dann, Mehryar Mohri, Tong Zhang, Julian Zimmert
2021	J	`jnl`	Adder Neural Networks. CoRR Hanting Chen, Yunhe Wang, Chang Xu, Chao Xu, Chunjing Xu, Tong Zhang
2021	J	`jnl`	DeEPCA: Decentralized Exact PCA with Linear Convergence Rate. CoRR Haishan Ye, Tong Zhang
2021	J	`jnl`	DeEPCA: Decentralized Exact PCA with Linear Convergence Rate. J. Mach. Learn. Res. Haishan Ye, Tong Zhang
2021	A*	`conf`	DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neural Networks. KDD Yuhui Ding, Quanming Yao, Huan Zhao, Tong Zhang
2021	A*	`conf`	Effective Sparsification of Neural Networks With Global Sparsity Constraint. CVPR Xiao Zhou, Weizhong Zhang, Hang Xu, Tong Zhang
2021	J	`jnl`	Effective Sparsification of Neural Networks with Global Sparsity Constraint. CoRR Xiao Zhou, Weizhong Zhang, Hang Xu, Tong Zhang
2021	A*	`conf`	Efficient Neural Network Training via Forward and Backward Propagation Sparsification. NeurIPS Xiao Zhou, Weizhong Zhang, Zonghao Chen, Shizhe Diao, Tong Zhang
2021	J	`jnl`	Efficient Neural Network Training via Forward and Backward Propagation Sparsification. CoRR Xiao Zhou, Weizhong Zhang, Zonghao Chen, Shizhe Diao, Tong Zhang
2021	J	`jnl`	Eigencurve: Optimal Learning Rate Schedule for SGD on Quadratic Objectives with Skewed Hessian Spectrums. CoRR Rui Pan, Haishan Ye, Tong Zhang
2021	A*	`conf`	Error Compensated Distributed SGD Can Be Accelerated. NeurIPS Xun Qian, Peter Richtárik, Tong Zhang
2021	J	`jnl`	Feel-Good Thompson Sampling for Contextual Bandits and Reinforcement Learning. CoRR Tong Zhang
2021	A*	`conf`	Few-Shot Human Motion Transfer by Personalized Geometry and Texture Modeling. CVPR Zhichao Huang, Xintong Han, Jia Xu, Tong Zhang
2021	J	`jnl`	Few-Shot Human Motion Transfer by Personalized Geometry and Texture Modeling. CoRR Zhichao Huang, Xintong Han, Jia Xu, Tong Zhang
2021	J	`jnl`	Finite-Sample Analysis for Decentralized Batch Multiagent Reinforcement Learning With Networked Agents. IEEE Trans. Autom. Control. Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Basar
2021	J	`jnl`	Frequency-Aware Contrastive Learning for Neural Machine Translation. CoRR Tong Zhang, Wei Ye, Baosong Yang, Long Zhang, Xingzhang Ren, Dayiheng Liu, Jinan Sun, Shikun Zhang, Haibo Zhang, Wen Zhao
2021	A*	`conf`	G-DetKD: Towards General Distillation Framework for Object Detectors via Contrastive and Semantic-guided Feature Imitation. ICCV Lewei Yao, Renjie Pi, Hang Xu, Wei Zhang, Zhenguo Li, Tong Zhang
2021	J	`jnl`	G-DetKD: Towards General Distillation Framework for Object Detectors via Contrastive and Semantic-guided Feature Imitation. CoRR Lewei Yao, Renjie Pi, Hang Xu, Wei Zhang, Zhenguo Li, Tong Zhang
2021	J	`jnl`	Geometry-aware data augmentation for monocular 3D object detection. CoRR Qing Lian, Botao Ye, Ruijia Xu, Weilong Yao, Tong Zhang
2021	Misc	`conf`	Improving Event Detection by Exploiting Label Hierarchy. ICASSP Xiangyu Xi, Wei Ye, Tong Zhang, Quanxiu Wang, Shikun Zhang, Huixing Jiang, Wei Wu
2021	A*	`conf`	Involution: Inverting the Inherence of Convolution for Visual Recognition. CVPR Duo Li, Jie Hu, Changhu Wang, Xiangtai Li, Qi She, Lei Zhu, Tong Zhang, Qifeng Chen
2021	J	`jnl`	Involution: Inverting the Inherence of Convolution for Visual Recognition. CoRR Duo Li, Jie Hu, Changhu Wang, Xiangtai Li, Qi She, Lei Zhu, Tong Zhang, Qifeng Chen
2021	A*	`conf`	Joint-DetNAS: Upgrade Your Detector With NAS, Pruning and Dynamic Distillation. CVPR Lewei Yao, Renjie Pi, Hang Xu, Wei Zhang, Zhenguo Li, Tong Zhang
2021	J	`jnl`	Joint-DetNAS: Upgrade Your Detector with NAS, Pruning and Dynamic Distillation. CoRR Lewei Yao, Renjie Pi, Hang Xu, Wei Zhang, Zhenguo Li, Tong Zhang
2021	J	`jnl`	Local-Global Memory Neural Network for Medication Prediction. IEEE Trans. Neural Networks Learn. Syst. Jun Song, Yueyang Wang, Siliang Tang, Yin Zhang, Zhigang Chen, Zhongfei Zhang, Tong Zhang, Fei Wu
2021	J	`jnl`	Mathematical Models of Overparameterized Neural Networks. Proc. IEEE Cong Fang, Hanze Dong, Tong Zhang
2021	A*	`conf`	Modeling from Features: a Mean-field Framework for Over-parameterized Deep Neural Networks. COLT Cong Fang, Jason D. Lee, Pengkun Yang, Tong Zhang
2021	—	`conf`	Multi-Hop Transformer for Document-Level Machine Translation. NAACL-HLT Long Zhang, Tong Zhang, Haibo Zhang, Baosong Yang, Wei Ye, Shikun Zhang
2021	J	`jnl`	Near Optimal Stochastic Algorithms for Finite-Sum Unbalanced Convex-Concave Minimax Optimization. CoRR Luo Luo, Guangzeng Xie, Tong Zhang, Zhihua Zhang
2021	—	`conf`	Point, Disambiguate and Copy: Incorporating Bilingual Dictionaries for Neural Machine Translation. ACL/IJCNLP (1) Tong Zhang, Long Zhang, Wei Ye, Bo Li, Jinan Sun, Xiaoyu Zhu, Wen Zhao, Shikun Zhang
2021	A*	`ed.`	Proceedings of the 38th International Conference on Machine Learning, ICML 2021, 18-24 July 2021, Virtual Event. ICML Marina Meila, Tong Zhang
2021	—	`conf`	TILGAN: Transformer-based Implicit Latent GAN for Diverse and Coherent Text Generation. ACL/IJCNLP (Findings) Shizhe Diao, Xinwei Shen, Kashun Shum, Yan Song, Tong Zhang
2021	—	`conf`	Taming Pre-trained Language Models with N-gram Representations for Low-Resource Domain Adaptation. ACL/IJCNLP (1) Shizhe Diao, Ruijia Xu, Hongjin Su, Yilei Jiang, Yan Song, Tong Zhang
2021	A*	`conf`	TransNAS-Bench-101: Improving Transferability and Generalizability of Cross-Task Neural Architecture Search. CVPR Yawen Duan, Xin Chen, Hang Xu, Zewei Chen, Xiaodan Liang, Tong Zhang, Zhenguo Li
2021	J	`jnl`	TransNAS-Bench-101: Improving Transferability and Generalizability of Cross-Task Neural Architecture Search. CoRR Yawen Duan, Xin Chen, Hang Xu, Zewei Chen, Xiaodan Liang, Tong Zhang, Zhenguo Li
2021	J	`jnl`	When is the Convergence Time of Langevin Algorithms Dimension Independent? A Composite Optimization Viewpoint. CoRR Yoav Freund, Yi-An Ma, Tong Zhang
2021	J	`jnl`	Why Stable Learning Works? A Theory of Covariate Shift Generalization. CoRR Renzhe Xu, Peng Cui, Zheyan Shen, Xingxuan Zhang, Tong Zhang
2021	J	`jnl`	ZEN 2.0: Continue Training and Adaption for N-gram Enhanced Text Encoders. CoRR Yan Song, Tong Zhang, Yonggang Wang, Kai-Fu Lee
2020	A*	`conf`	A Generalized Neural Tangent Kernel Analysis for Two-layer Neural Networks. NeurIPS Zixiang Chen, Yuan Cao, Quanquan Gu, Tong Zhang
2020	J	`jnl`	Accelerated Dual-Averaging Primal-Dual Method for Composite Convex Minimization. CoRR Conghui Tan, Yuqiu Qian, Shiqian Ma, Tong Zhang
2020	J	`jnl`	Accelerated dual-averaging primal-dual method for composite convex minimization. Optim. Methods Softw. Conghui Tan, Yuqiu Qian, Shiqian Ma, Tong Zhang
2020	J	`jnl`	Bidirectional Generative Modeling Using Adversarial Gradient Estimation. CoRR Xinwei Shen, Tong Zhang, Kani Chen
2020	A*	`conf`	Black-Box Adversarial Attack with Transferable Model-based Embedding. ICLR Zhichao Huang, Tong Zhang
2020	A*	`conf`	Bridging the Gap between Sample-based and One-shot Neural Architecture Search with BONAS. NeurIPS Han Shi, Renjie Pi, Hang Xu, Zhenguo Li, James T. Kwok, Tong Zhang
2020	—	`conf`	CATCH: Context-Based Meta Reinforcement Learning for Transferrable Architecture Search. ECCV (19) Xin Chen, Yawen Duan, Zewei Chen, Hang Xu, Zihao Chen, Xiaodan Liang, Tong Zhang, Zhenguo Li
2020	J	`jnl`	CATCH: Context-based Meta Reinforcement Learning for Transferrable Architecture Search. CoRR Xin Chen, Yawen Duan, Zewei Chen, Hang Xu, Zihao Chen, Xiaodan Liang, Tong Zhang, Zhenguo Li
2020	J	`jnl`	CorrAttack: Black-box Adversarial Attack with Structured Search. CoRR Zhichao Huang, Yaowei Huang, Tong Zhang
2020	A*	`conf`	Decentralized Accelerated Proximal Gradient Descent. NeurIPS Haishan Ye, Ziang Zhou, Luo Luo, Tong Zhang
2020	J	`jnl`	Disentangled Generative Causal Representation Learning. CoRR Xinwei Shen, Furui Liu, Hanze Dong, Qing Lian, Zhitang Chen, Tong Zhang
2020	J	`jnl`	End-to-End Active Object Tracking and Its Real-World Deployment via Reinforcement Learning. IEEE Trans. Pattern Anal. Mach. Intell. Wenhan Luo, Peng Sun, Fangwei Zhong, Wei Liu, Tong Zhang, Yizhou Wang
2020	A*	`conf`	Guided Learning of Nonconvex Models through Successive Functional Gradient Optimization. ICML Rie Johnson, Tong Zhang
2020	J	`jnl`	Guided Learning of Nonconvex Models through Successive Functional Gradient Optimization. CoRR Rie Johnson, Tong Zhang
2020	A*	`conf`	How to Characterize The Landscape of Overparameterized Convolutional Neural Networks. NeurIPS Yihong Gu, Weizhong Zhang, Cong Fang, Jason D. Lee, Tong Zhang
2020	A*	`conf`	Improving Chinese Word Segmentation with Wordhood Memory Networks. ACL Yuanhe Tian, Yan Song, Fei Xia, Tong Zhang, Yonggang Wang
2020	—	`conf`	Improving Constituency Parsing with Span Attention. EMNLP (Findings) Yuanhe Tian, Yan Song, Fei Xia, Tong Zhang
2020	J	`jnl`	Improving Constituency Parsing with Span Attention. CoRR Yuanhe Tian, Yan Song, Fei Xia, Tong Zhang
2020	A*	`conf`	Joint Chinese Word Segmentation and Part-of-speech Tagging via Two-way Attentions of Auto-analyzed Knowledge. ACL Yuanhe Tian, Yan Song, Xiang Ao, Fei Xia, Xiaojun Quan, Tong Zhang, Yonggang Wang
2020	A	`conf`	Leveraging Human Prior Knowledge to Learn Sense Representations. ECAI Tong Zhang, Wei Ye, Xiangyu Xi, Long Zhang, Shikun Zhang, Wen Zhao
2020	J	`jnl`	MAP Inference Via ℓ Int. J. Comput. Vis. Baoyuan Wu, Li Shen, Tong Zhang, Bernard Ghanem
2020	J	`jnl`	Mathematical Models of Overparameterized Neural Networks. CoRR Cong Fang, Hanze Dong, Tong Zhang
2020	J	`jnl`	Mean-Field Analysis of Two-Layer Neural Networks: Non-Asymptotic Rates and Generalization Bounds. CoRR Zixiang Chen, Yuan Cao, Quanquan Gu, Tong Zhang
2020	A*	`conf`	MiLeNAS: Efficient Neural Architecture Search via Mixed-Level Reformulation. CVPR Chaoyang He, Haishan Ye, Li Shen, Tong Zhang
2020	J	`jnl`	MiLeNAS: Efficient Neural Architecture Search via Mixed-Level Reformulation. CoRR Chaoyang He, Haishan Ye, Li Shen, Tong Zhang
2020	A*	`conf`	Model Rubik's Cube: Twisting Resolution, Depth and Width for TinyNets. NeurIPS Kai Han, Yunhe Wang, Qiulin Zhang, Wei Zhang, Chunjing Xu, Tong Zhang
2020	J	`jnl`	Model Rubik's Cube: Twisting Resolution, Depth and Width for TinyNets. CoRR Kai Han, Yunhe Wang, Qiulin Zhang, Wei Zhang, Chunjing Xu, Tong Zhang
2020	J	`jnl`	Modeling from Features: a Mean-field Framework for Over-parameterized Deep Neural Networks. CoRR Cong Fang, Jason D. Lee, Pengkun Yang, Tong Zhang
2020	J	`jnl`	Multi-consensus Decentralized Accelerated Gradient Descent. CoRR Haishan Ye, Luo Luo, Ziang Zhou, Tong Zhang
2020	J	`jnl`	Multi-modal AsynDGAN: Learn From Distributed Medical Image Data without Sharing Private Information. CoRR Qi Chang, Zhennan Yan, Lohendran Baskaran, Hui Qu, Yikai Zhang, Tong Zhang, Shaoting Zhang, Dimitris N. Metaxas
2020	J	`jnl`	PMGT-VR: A decentralized proximal-gradient algorithmic framework with variance reduction. CoRR Haishan Ye, Wei Xiong, Tong Zhang
2020	J	`jnl`	Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python. CoRR Jason Ge, Xingguo Li, Haoming Jiang, Han Liu, Tong Zhang, Mengdi Wang, Tuo Zhao
2020	J	`jnl`	Propagation Model Search for Graph Neural Networks. CoRR Yuhui Ding, Quanming Yao, Tong Zhang
2020	J	`jnl`	Proximal Gradient Method for Nonsmooth Optimization over the Stiefel Manifold. SIAM J. Optim. Shixiang Chen, Shiqian Ma, Anthony Man-Cho So, Tong Zhang
2020	A*	`conf`	Residual Distillation: Towards Portable Deep Neural Networks without Shortcuts. NeurIPS Guilin Li, Junlei Zhang, Yunhe Wang, Chuanjian Liu, Matthias Tan, Yunfeng Lin, Wei Zhang, Jiashi Feng, Tong Zhang
2020	A*	`conf`	Stable Learning via Differentiated Variable Decorrelation. KDD Zheyan Shen, Peng Cui, Jiashuo Liu, Tong Zhang, Bo Li, Zhitang Chen
2020	A*	`conf`	Stable Learning via Sample Reweighting. AAAI Zheyan Shen, Peng Cui, Tong Zhang, Kun Kuang
2020	A*	`conf`	Stochastic Recursive Gradient Descent Ascent for Stochastic Nonconvex-Strongly-Concave Minimax Problems. NeurIPS Luo Luo, Haishan Ye, Zhichao Huang, Tong Zhang
2020	J	`jnl`	Stochastic Recursive Gradient Descent Ascent for Stochastic Nonconvex-Strongly-Concave Minimax Problems. CoRR Luo Luo, Haishan Ye, Tong Zhang
2020	A*	`conf`	Synthetic Learning: Learn From Distributed Asynchronized Discriminator GAN Without Sharing Medical Image Data. CVPR Qi Chang, Hui Qu, Yikai Zhang, Mert R. Sabuncu, Chao Chen, Tong Zhang, Dimitris N. Metaxas
2020	J	`jnl`	Synthetic Learning: Learn From Distributed Asynchronized Discriminator GAN Without Sharing Medical Image Data. CoRR Qi Chang, Hui Qu, Yikai Zhang, Mert R. Sabuncu, Chao Chen, Tong Zhang, Dimitris N. Metaxas
2020	J	`jnl`	VEGA: Towards an End-to-End Configurable AutoML Pipeline. CoRR Bochao Wang, Hang Xu, Jiajin Zhang, Chen Chen, Yixing Xu, Xiaozhi Fang, Ning Kang, Lanqing Hong, Chenhan Jiang, Xinyue Cai, Jiawei Li, Fengwei Zhou, Yong Li, Zhicheng Liu, Xinghao Chen, Kai Han, Han Shu, Dehua Song, Yunhe Wang, Wei Zhang, Chunjing Xu, Zhenguo Li, Wenzhi Liu, Tong Zhang
2020	—	`conf`	ZEN: Pre-training Chinese Text Encoder Enhanced by N-gram Representations. EMNLP (Findings) Shizhe Diao, Jiaxin Bai, Yan Song, Tong Zhang, Yonggang Wang
2019	B	`conf`	A Hybrid Character Representation for Chinese Event Detection. IJCNN Xiangyu Xi, Tong Zhang, Wei Ye, Jinglei Zhang, Rui Xie, Shikun Zhang
2019	J	`jnl`	Black-Box Adversarial Attack with Transferable Model-based Embedding. CoRR Zhichao Huang, Tong Zhang
2019	J	`jnl`	Convex Formulation of Overparameterized Deep Neural Networks. CoRR Cong Fang, Yihong Gu, Weizhong Zhang, Tong Zhang
2019	—	`conf`	DHER: Hindsight Experience Replay for Dynamic Goals. ICLR (Poster) Meng Fang, Cheng Zhou, Bei Shi, Boqing Gong, Jia Xu, Tong Zhang
2019	J	`jnl`	DeepSqueeze: Parallel Stochastic Gradient Descent with Double-Pass Error-Compensated Compression. CoRR Hanlin Tang, Xiangru Lian, Shuang Qiu, Lei Yuan, Ce Zhang, Tong Zhang, Ji Liu
2019	A*	`conf`	Divergence-Augmented Policy Optimization. NeurIPS Qing Wang, Yingru Li, Jiechao Xiong, Tong Zhang
2019	J	`jnl`	DoubleSqueeze: Parallel Stochastic Gradient Descent with Double-Pass Error-Compensated Compression. CoRR Hanlin Tang, Xiangru Lian, Tong Zhang, Ji Liu
2019	A*	`conf`	DoubleSqueeze: Parallel Stochastic Gradient Descent with Double-pass Error-Compensated Compression. ICML Hanlin Tang, Chen Yu, Xiangru Lian, Tong Zhang, Ji Liu
2019	A*	`conf`	Dynamic Layer Aggregation for Neural Machine Translation with Routing-by-Agreement. AAAI Zi-Yi Dou, Zhaopeng Tu, Xing Wang, Longyue Wang, Shuming Shi, Tong Zhang
2019	J	`jnl`	Dynamic Layer Aggregation for Neural Machine Translation with Routing-by-Agreement. CoRR Zi-Yi Dou, Zhaopeng Tu, Xing Wang, Longyue Wang, Shuming Shi, Tong Zhang
2019	A*	`conf`	Efficient Decision-Based Black-Box Adversarial Attacks on Face Recognition. CVPR Yinpeng Dong, Hang Su, Baoyuan Wu, Zhifeng Li, Wei Liu, Tong Zhang, Jun Zhu
2019	J	`jnl`	Efficient Decision-based Black-box Adversarial Attacks on Face Recognition. CoRR Yinpeng Dong, Hang Su, Baoyuan Wu, Zhifeng Li, Wei Liu, Tong Zhang, Jun Zhu
2019	J	`jnl`	Fast Generalized Matrix Regression with Applications in Machine Learning. CoRR Haishan Ye, Shusen Wang, Zhihua Zhang, Tong Zhang
2019	J	`jnl`	Graph-guided multi-task sparse learning model: a method for identifying antigenic variants of influenza A(H3N2) virus. Bioinform. Lei Han, Lei Li, Feng Wen, Lei Zhong, Tong Zhang, Xiu-Feng Wan
2019	A*	`conf`	Grid-Wise Control for Multi-Agent Reinforcement Learning in Video Game AI. ICML Lei Han, Peng Sun, Yali Du, Jiechao Xiong, Qing Wang, Xinghai Sun, Han Liu, Tong Zhang
2019	J	`jnl`	Layer-Wise Learning Strategy for Nonparametric Tensor Product Smoothing Spline Regression and Graphical Models. J. Mach. Learn. Res. Kean Ming Tan, Junwei Lu, Tong Zhang, Han Liu
2019	J	`jnl`	MAP Inference via L2-Sphere Linear Program Reformulation. CoRR Baoyuan Wu, Li Shen, Bernard Ghanem, Tong Zhang
2019	J	`jnl`	Mirror Natural Evolution Strategies. CoRR Haishan Ye, Tong Zhang
2019	J	`jnl`	Multi-objective Neural Architecture Search via Predictive Network Performance Optimization. CoRR Han Shi, Renjie Pi, Hang Xu, Zhenguo Li, James T. Kwok, Tong Zhang
2019	A*	`conf`	NATTACK: Learning the Distributions of Adversarial Examples for an Improved Black-Box Attack on Deep Neural Networks. ICML Yandong Li, Lijun Li, Liqiang Wang, Tong Zhang, Boqing Gong
2019	J	`jnl`	NATTACK: Learning the Distributions of Adversarial Examples for an Improved Black-Box Attack on Deep Neural Networks. CoRR Yandong Li, Lijun Li, Liqiang Wang, Tong Zhang, Boqing Gong
2019	A*	`conf`	Neural Machine Translation with Adequacy-Oriented Learning. AAAI Xiang Kong, Zhaopeng Tu, Shuming Shi, Eduard H. Hovy, Tong Zhang
2019	J	`jnl`	Over Parameterized Two-level Neural Networks Can Learn Near Optimal Feature Representations. CoRR Cong Fang, Hanze Dong, Tong Zhang
2019	J	`jnl`	Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python. J. Mach. Learn. Res. Jason Ge, Xingguo Li, Haoming Jiang, Han Liu, Tong Zhang, Mengdi Wang, Tuo Zhao
2019	—	`conf`	Reinforced Training Data Selection for Domain Adaptation. ACL (1) Miaofeng Liu, Yan Song, HongBin Zou, Tong Zhang
2019	J	`jnl`	Robust Frequent Directions with Application in Online Learning. J. Mach. Learn. Res. Luo Luo, Cheng Chen, Zhihua Zhang, Wu-Jun Li, Tong Zhang
2019	—	`conf`	Sentiment Analysis Using Autoregressive Language Modeling and Broad Learning System. BIBM Xin-Rong Gong, Jian-Xiu Jin, Tong Zhang
2019	A*	`conf`	Sharp Analysis for Nonconvex SGD Escaping from Saddle Points. COLT Cong Fang, Zhouchen Lin, Tong Zhang
2019	J	`jnl`	Sharp Analysis for Nonconvex SGD Escaping from Saddle Points. CoRR Cong Fang, Zhouchen Lin, Tong Zhang
2019	J	`jnl`	Spatial Sparse subspace clustering for Compressive Spectral imaging. CoRR Jianchen Zhu, Tong Zhang, Shengjie Zhao, Carlos Hinojosa, Zengli Liu, Gonzalo R. Arce
2019	J	`jnl`	Stable Learning via Sample Reweighting. CoRR Zheyan Shen, Peng Cui, Tong Zhang, Kun Kuang
2019	J	`jnl`	StacNAS: Towards stable and consistent optimization for differentiable Neural Architecture Search. CoRR Guilin Li, Xing Zhang, Zitong Wang, Zhenguo Li, Tong Zhang
2019	J	`jnl`	Tencent ML-Images: A Large-Scale Multi-Label Image Database for Visual Representation Learning. IEEE Access Baoyuan Wu, Weidong Chen, Yanbo Fan, Yong Zhang, Jinlong Hou, Jie Liu, Tong Zhang
2019	J	`jnl`	Tencent ML-Images: A Large-Scale Multi-Label Image Database for Visual Representation Learning. CoRR Baoyuan Wu, Weidong Chen, Yanbo Fan, Yong Zhang, Jinlong Hou, Jie Liu, Junzhou Huang, Wei Liu, Tong Zhang
2019	J	`jnl`	Utilizing Second Order Information in Minibatch Stochastic Variance Reduced Proximal Iterations. J. Mach. Learn. Res. Jialei Wang, Tong Zhang
2019	J	`jnl`	ZEN: Pre-training Chinese Text Encoder Enhanced by N-gram Representations. CoRR Shizhe Diao, Jiaxin Bai, Yan Song, Tong Zhang, Yonggang Wang
2018	J	`jnl`	A convex formulation for high-dimensional sparse sliced inverse regression. CoRR Kean Ming Tan, Zhaoran Wang, Tong Zhang, Han Liu, R. Dennis Cook
2018	A*	`conf`	An Algorithmic Framework of Variable Metric Over-Relaxed Hybrid Proximal Extra-Gradient Method. ICML Li Shen, Peng Sun, Yitong Wang, Wei Liu, Tong Zhang
2018	J	`jnl`	An Algorithmic Framework of Variable Metric Over-Relaxed Hybrid Proximal Extra-Gradient Method. CoRR Li Shen, Peng Sun, Yitong Wang, Wei Liu, Tong Zhang
2018	J	`jnl`	An Ensemble Approach for Detecting Anomalous User Behaviors. Int. J. Softw. Eng. Knowl. Eng. Xiangyu Xi, Tong Zhang, Wei Ye, Wen Zhao, Shikun Zhang, Dongdong Du, Qing Gao
2018	J	`jnl`	Bayesian Model Averaging With Exponentiated Least Squares Loss. IEEE Trans. Inf. Theory Dong Dai, Lei Han, Ting Yang, Tong Zhang
2018	A*	`conf`	Candidates vs. Noises Estimation for Large Multi-Class Classification Problem. ICML Lei Han, Yiheng Huang, Tong Zhang
2018	A*	`conf`	Communication Compression for Decentralized Training. NeurIPS Hanlin Tang, Shaoduo Gan, Ce Zhang, Tong Zhang, Ji Liu
2018	A*	`conf`	Composite Functional Gradient Learning of Generative Adversarial Models. ICML Rie Johnson, Tong Zhang
2018	J	`jnl`	Composite Functional Gradient Learning of Generative Adversarial Models. CoRR Rie Johnson, Tong Zhang
2018	J	`jnl`	Decentralization Meets Quantization. CoRR Hanlin Tang, Ce Zhang, Shaoduo Gan, Tong Zhang, Ji Liu
2018	J	`jnl`	Diffusion Approximations for Online Principal Component Estimation and Global Convergence. CoRR Chris Junchi Li, Mengdi Wang, Han Liu, Tong Zhang
2018	J	`jnl`	End-to-end Active Object Tracking and Its Real-world Deployment via Reinforcement Learning. CoRR Wenhan Luo, Peng Sun, Fangwei Zhong, Wei Liu, Tong Zhang, Yizhou Wang
2018	A*	`conf`	End-to-end Active Object Tracking via Reinforcement Learning. ICML Wenhan Luo, Peng Sun, Fangwei Zhong, Wei Liu, Tong Zhang, Yizhou Wang
2018	A*	`conf`	Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization. ICML Jiaxiang Wu, Weidong Huang, Junzhou Huang, Tong Zhang
2018	J	`jnl`	Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization. CoRR Jiaxiang Wu, Weidong Huang, Junzhou Huang, Tong Zhang
2018	A*	`conf`	Exploiting Deep Representations for Neural Machine Translation. EMNLP Zi-Yi Dou, Zhaopeng Tu, Xing Wang, Shuming Shi, Tong Zhang
2018	J	`jnl`	Exploiting Deep Representations for Neural Machine Translation. CoRR Zi-Yi Dou, Zhaopeng Tu, Xing Wang, Shuming Shi, Tong Zhang
2018	A*	`conf`	Exponentially Weighted Imitation Learning for Batched Historical Data. NeurIPS Qing Wang, Jiechao Xiong, Lei Han, Peng Sun, Han Liu, Tong Zhang
2018	—	`conf`	Fine-grained Video Attractiveness Prediction Using Multimodal Deep Learning on a Large Real-world Dataset. WWW (Companion Volume) Xinpeng Chen, Jingyuan Chen, Lin Ma, Jian Yao, Wei Liu, Jiebo Luo, Tong Zhang
2018	J	`jnl`	Fine-grained Video Attractiveness Prediction Using Multimodal Deep Learning on a Large Real-world Dataset. CoRR Xinpeng Chen, Jingyuan Chen, Lin Ma, Jian Yao, Wei Liu, Jiebo Luo, Tong Zhang
2018	J	`jnl`	Finite-Sample Analyses for Fully Decentralized Multi-Agent Reinforcement Learning. CoRR Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Basar
2018	A*	`conf`	Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents. ICML Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Basar
2018	J	`jnl`	Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents. CoRR Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Basar
2018	J	`jnl`	Fully Implicit Online Learning. CoRR Chao-Bing Song, Ji Liu, Han Liu, Yong Jiang, Tong Zhang
2018	A*	`conf`	Gradient Sparsification for Communication-Efficient Distributed Optimization. NeurIPS Jianqiao Wangni, Jialei Wang, Ji Liu, Tong Zhang
2018	A*	`conf`	Graphical Nonconvex Optimization via an Adaptive Convex Relaxation. ICML Qiang Sun, Kean Ming Tan, Han Liu, Tong Zhang
2018	J	`jnl`	Hessian-Aware Zeroth-Order Optimization for Black-Box Adversarial Attack. CoRR Haishan Ye, Zhichao Huang, Cong Fang, Chris Junchi Li, Tong Zhang
2018	J	`jnl`	Incorporating Pseudo-Parallel Data for Quantifiable Sequence Editing. CoRR Yi Liao, Lidong Bing, Piji Li, Shuming Shi, Wai Lam, Tong Zhang
2018	J	`jnl`	Learning to Remember Translation History with a Continuous Cache. Trans. Assoc. Comput. Linguistics Zhaopeng Tu, Yang Liu, Shuming Shi, Tong Zhang
2018	A*	`conf`	Modeling Localness for Self-Attention Networks. EMNLP Baosong Yang, Zhaopeng Tu, Derek F. Wong, Fandong Meng, Lidia S. Chao, Tong Zhang
2018	J	`jnl`	Modeling Localness for Self-Attention Networks. CoRR Baosong Yang, Zhaopeng Tu, Derek F. Wong, Fandong Meng, Lidia S. Chao, Tong Zhang
2018	—	`conf`	Modeling Varying Camera-IMU Time Offset in Optimization-Based Visual-Inertial Odometry. ECCV (9) Yonggen Ling, Linchao Bao, Zequn Jie, Fengming Zhu, Ziyang Li, Shanmin Tang, Yongsheng Liu, Wei Liu, Tong Zhang
2018	J	`jnl`	Modeling Varying Camera-IMU Time Offset in Optimization-Based Visual-Inertial Odometry. CoRR Yonggen Ling, Linchao Bao, Zequn Jie, Fengming Zhu, Ziyang Li, Shanmin Tang, Yongsheng Liu, Wei Liu, Tong Zhang
2018	A*	`conf`	Multi-Head Attention with Disagreement Regularization. EMNLP Jian Li, Zhaopeng Tu, Baosong Yang, Michael R. Lyu, Tong Zhang
2018	J	`jnl`	Multi-Head Attention with Disagreement Regularization. CoRR Jian Li, Zhaopeng Tu, Baosong Yang, Michael R. Lyu, Tong Zhang
2018	J	`jnl`	Near-optimal stochastic approximation for online principal component estimation. Math. Program. Chris Junchi Li, Mengdi Wang, Han Liu, Tong Zhang
2018	J	`jnl`	Neural Machine Translation with Adequacy-Oriented Learning. CoRR Xiang Kong, Zhaopeng Tu, Shuming Shi, Eduard H. Hovy, Tong Zhang
2018	—	`conf`	Neural Stereoscopic Image Style Transfer. ECCV (5) Xinyu Gong, Haozhi Huang, Lin Ma, Fumin Shen, Wei Liu, Tong Zhang
2018	J	`jnl`	Neural Stereoscopic Image Style Transfer. CoRR Xinyu Gong, Haozhi Huang, Lin Ma, Fumin Shen, Wei Liu, Tong Zhang
2018	—	`conf`	Orthogonal Deep Features Decomposition for Age-Invariant Face Recognition. ECCV (15) Yitong Wang, Dihong Gong, Zheng Zhou, Xing Ji, Hao Wang, Zhifeng Li, Wei Liu, Tong Zhang
2018	J	`jnl`	Orthogonal Deep Features Decomposition for Age-Invariant Face Recognition. CoRR Yitong Wang, Dihong Gong, Zheng Zhou, Xing Ji, Hao Wang, Zhifeng Li, Wei Liu, Tong Zhang
2018	J	`jnl`	Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Space. CoRR Jiechao Xiong, Qing Wang, Zhuoran Yang, Peng Sun, Lei Han, Yang Zheng, Haobo Fu, Tong Zhang, Ji Liu, Han Liu
2018	A*	`conf`	QuaSE: Sequence Editing under Quantifiable Guidance. EMNLP Yi Liao, Lidong Bing, Piji Li, Shuming Shi, Wai Lam, Tong Zhang
2018	—	`conf`	Recurrent Fusion Network for Image Captioning. ECCV (2) Wenhao Jiang, Lin Ma, Yu-Gang Jiang, Wei Liu, Tong Zhang
2018	J	`jnl`	Recurrent Fusion Network for Image Captioning. CoRR Wenhao Jiang, Lin Ma, Yu-Gang Jiang, Wei Liu, Tong Zhang
2018	J	`jnl`	SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path Integrated Differential Estimator. CoRR Cong Fang, Chris Junchi Li, Zhouchen Lin, Tong Zhang
2018	A*	`conf`	SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path-Integrated Differential Estimator. NeurIPS Cong Fang, Chris Junchi Li, Zhouchen Lin, Tong Zhang
2018	A*	`conf`	Safe Element Screening for Submodular Function Minimization. ICML Weizhong Zhang, Bin Hong, Lin Ma, Wei Liu, Tong Zhang
2018	J	`jnl`	Safe Element Screening for Submodular Function Minimization. CoRR Weizhong Zhang, Bin Hong, Lin Ma, Wei Liu, Tong Zhang
2018	A*	`conf`	Sketched Follow-The-Regularized-Leader for Online Factorization Machine. KDD Luo Luo, Wenpeng Zhang, Zhihua Zhang, Wenwu Zhu, Tong Zhang, Jian Pei
2018	A*	`conf`	Stochastic Expectation Maximization with Variance Reduction. NeurIPS Jianfei Chen, Jun Zhu, Yee Whye Teh, Tong Zhang
2018	A*	`conf`	Stochastic Primal-Dual Method for Empirical Risk Minimization with O(1) Per-Iteration Complexity. NeurIPS Conghui Tan, Tong Zhang, Shiqian Ma, Ji Liu
2018	J	`jnl`	Stochastic Primal-Dual Method for Empirical Risk Minimization with O(1) Per-Iteration Complexity. CoRR Conghui Tan, Tong Zhang, Shiqian Ma, Ji Liu
2018	—	`conf`	Super-Identity Convolutional Neural Network for Face Hallucination. ECCV (11) Kaipeng Zhang, Zhanpeng Zhang, Chia-Wen Cheng, Winston H. Hsu, Yu Qiao, Wei Liu, Tong Zhang
2018	J	`jnl`	Super-Identity Convolutional Neural Network for Face Hallucination. CoRR Kaipeng Zhang, Zhanpeng Zhang, Chia-Wen Cheng, Winston H. Hsu, Yu Qiao, Wei Liu, Tong Zhang
2018	J	`jnl`	TStarBots: Defeating the Cheating Level Builtin AI in StarCraft II in the Full Game. CoRR Peng Sun, Xinghai Sun, Lei Han, Jiechao Xiong, Qing Wang, Bo Li, Yang Zheng, Ji Liu, Yongsheng Liu, Han Liu, Tong Zhang
2018	A*	`conf`	Translating Pro-Drop Languages With Reconstruction Models. AAAI Longyue Wang, Zhaopeng Tu, Shuming Shi, Tong Zhang, Yvette Graham, Qun Liu
2018	J	`jnl`	Translating Pro-Drop Languages with Reconstruction Models. CoRR Longyue Wang, Zhaopeng Tu, Shuming Shi, Tong Zhang, Yvette Graham, Qun Liu
2018	—	`conf`	Unsupervised Image-to-Image Translation with Stacked Cycle-Consistent Adversarial Networks. ECCV (9) Minjun Li, Haozhi Huang, Lin Ma, Wei Liu, Tong Zhang, Yu-Gang Jiang
2018	J	`jnl`	Unsupervised Image-to-Image Translation with Stacked Cycle-Consistent Adversarial Networks. CoRR Minjun Li, Haozhi Huang, Lin Ma, Wei Liu, Tong Zhang, Yu-Gang Jiang
2018	—	`conf`	Video Re-localization. ECCV (14) Yang Feng, Lin Ma, Wei Liu, Tong Zhang, Jiebo Luo
2018	J	`jnl`	Video Re-localization. CoRR Yang Feng, Lin Ma, Wei Liu, Tong Zhang, Jiebo Luo
2017	J	`jnl`	A General Distributed Dual Coordinate Optimization Framework for Regularized Loss Minimization. J. Mach. Learn. Res. Shun Zheng, Jialei Wang, Fen Xia, Wei Xu, Tong Zhang
2017	J	`jnl`	Candidates v.s. Noises Estimation for Large Multi-Class Classification Problem. CoRR Lei Han, Tong Zhang
2017	—	`conf`	Deep Pyramid Convolutional Neural Networks for Text Categorization. ACL (1) Rie Johnson, Tong Zhang
2017	—	`conf`	Diffusion Approximations for Online Principal Component Estimation and Global Convergence. NIPS Chris Junchi Li, Mengdi Wang, Tong Zhang
2017	A*	`conf`	Efficient Distributed Learning with Sparsity. ICML Jialei Wang, Mladen Kolar, Nathan Srebro, Tong Zhang
2017	J	`jnl`	Gradient Hard Thresholding Pursuit. J. Mach. Learn. Res. Xiao-Tong Yuan, Ping Li, Tong Zhang
2017	J	`jnl`	Gradient Sparsification for Communication-Efficient Distributed Optimization. CoRR Jianqiao Wangni, Jialei Wang, Ji Liu, Tong Zhang
2017	J	`jnl`	Hierarchical Contextual Attention Recurrent Neural Network for Map Query Suggestion. IEEE Trans. Knowl. Data Eng. Jun Song, Jun Xiao, Fei Wu, Haishan Wu, Tong Zhang, Zhongfei (Mark) Zhang, Wenwu Zhu
2017	J	`jnl`	Improved Optimization of Finite Sums with Minibatch Stochastic Variance Reduced Proximal Iterations. CoRR Jialei Wang, Tong Zhang
2017	J	`jnl`	Learning to Remember Translation History with a Continuous Cache. CoRR Zhaopeng Tu, Yang Liu, Shuming Shi, Tong Zhang
2017	J	`jnl`	On Quadratic Convergence of DC Proximal Newton Algorithm for Nonconvex Sparse Learning in High Dimensions. CoRR Xingguo Li, Lin F. Yang, Jason Ge, Jarvis D. Haupt, Tong Zhang, Tuo Zhao
2017	—	`conf`	On Quadratic Convergence of DC Proximal Newton Algorithm in Nonconvex Sparse Learning. NIPS Xingguo Li, Lin Yang, Jason Ge, Jarvis D. Haupt, Tong Zhang, Tuo Zhao
2017	A*	`conf`	Projection-free Distributed Online Learning in Networks. ICML Wenpeng Zhang, Peilin Zhao, Wenwu Zhu, Steven C. H. Hoi, Tong Zhang
2017	J	`jnl`	Sparseness Analysis in the Pretraining of Deep Neural Networks. IEEE Trans. Neural Networks Learn. Syst. Jun Li, Tong Zhang, Wei Luo, Jian Yang, Xiao-Tong Yuan, Jian Zhang
2016	J	`jnl`	A General Distributed Dual Coordinate Optimization Framework for Regularized Loss Minimization. CoRR Shun Zheng, Fen Xia, Wei Xu, Tong Zhang
2016	J	`jnl`	Accelerated proximal stochastic dual coordinate ascent for regularized loss minimization. Math. Program. Shai Shalev-Shwartz, Tong Zhang
2016	J	`jnl`	Convolutional Neural Networks for Text Categorization: Shallow Word-level vs. Deep Character-level. CoRR Rie Johnson, Tong Zhang
2016	J	`jnl`	Efficient Distributed Learning with Sparsity. CoRR Jialei Wang, Mladen Kolar, Nathan Srebro, Tong Zhang
2016	—	`conf`	Exact Recovery of Hard Thresholding Pursuit. NIPS Xiao-Tong Yuan, Ping Li, Tong Zhang
2016	A*	`conf`	Fast Component Pursuit for Large-Scale Inverse Covariance Estimation. KDD Lei Han, Yu Zhang, Tong Zhang
2016	A*	`conf`	Generalized Hierarchical Sparse Model for Arbitrary-Order Interactive Antigenic Sites Identification in Flu Virus Data. KDD Lei Han, Yu Zhang, Xiu-Feng Wan, Tong Zhang
2016	—	`conf`	Learning Additive Exponential Family Graphical Models via \ell_{2, 1}-norm Regularized M-Estimation. NIPS Xiao-Tong Yuan, Ping Li, Tong Zhang, Qingshan Liu, Guangcan Liu
2016	J	`jnl`	Local Uncertainty Sampling for Large-Scale Multi-Class Logistic Regression. CoRR Lei Han, Ting Yang, Tong Zhang
2016	A*	`conf`	Sparse Nonlinear Regression: Parameter Estimation under Nonconvexity. ICML Zhuoran Yang, Zhaoran Wang, Han Liu, Yonina C. Eldar, Tong Zhang
2016	A*	`conf`	Supervised and Semi-Supervised Text Categorization using LSTM for Region Embeddings. ICML Rie Johnson, Tong Zhang
2016	J	`jnl`	Supervised and Semi-Supervised Text Categorization using One-Hot LSTM for Region Embeddings. CoRR Rie Johnson, Tong Zhang
2016	J	`jnl`	Towards More Efficient SPSD Matrix Approximation and CUR Matrix Decomposition. J. Mach. Learn. Res. Shusen Wang, Zhihua Zhang, Tong Zhang
2015	A*	`conf`	Adaptive Stochastic Alternating Direction Method of Multipliers. ICML Peilin Zhao, Jinwei Yang, Tong Zhang, Ping Li
2015	A*	`conf`	Crowd Fraud Detection in Internet Advertising. WWW Tian Tian, Jun Zhu, Fen Xia, Xin Zhuang, Tong Zhang
2015	—	`conf`	Effective Use of Word Order for Text Categorization with Convolutional Neural Networks. HLT-NAACL Rie Johnson, Tong Zhang
2015	—	`book`	Fundamentals of Predictive Text Mining, Second Edition Sholom M. Weiss, Nitin Indurkhya, Tong Zhang
2015	J	`jnl`	Improved Analyses of the Randomized Power Method and Block Lanczos Method. CoRR Shusen Wang, Zhihua Zhang, Tong Zhang
2015	J	`jnl`	Learning sparse low-threshold linear classifiers. J. Mach. Learn. Res. Sivan Sabato, Shai Shalev-Shwartz, Nathan Srebro, Daniel J. Hsu, Tong Zhang
2015	—	`conf`	Local Smoothness in Variance Reduced Optimization. NIPS Daniel Vainsencher, Han Liu, Tong Zhang
2015	—	`conf`	Quartz: Randomized Dual Coordinate Ascent with Arbitrary Sampling. NIPS Zheng Qu, Peter Richtárik, Tong Zhang
2015	J	`jnl`	Semi-Supervised Learning with Multi-View Embedding: Theory and Application with Convolutional Neural Networks. CoRR Rie Johnson, Tong Zhang
2015	—	`conf`	Semi-supervised Convolutional Neural Networks for Text Categorization via Region Embedding. NIPS Rie Johnson, Tong Zhang
2015	J	`jnl`	Sparse Nonlinear Regression: Parameter Estimation and Asymptotic Inference. CoRR Zhuoran Yang, Zhaoran Wang, Han Liu, Yonina C. Eldar, Tong Zhang
2015	A*	`conf`	Stochastic Optimization with Importance Sampling for Regularized Loss Minimization. ICML Peilin Zhao, Tong Zhang
2015	J	`jnl`	Towards More Efficient Nystrom Approximation and CUR Matrix Decomposition. CoRR Shusen Wang, Zhihua Zhang, Tong Zhang
2014	A*	`conf`	A Convergence Rate Analysis for LogitBoost, MART and Their Variant. ICML Peng Sun, Tong Zhang, Jie Zhou
2014	J	`jnl`	A Proximal Stochastic Gradient Method with Progressive Variance Reduction. SIAM J. Optim. Lin Xiao, Tong Zhang
2014	A*	`conf`	Accelerated Proximal Stochastic Dual Coordinate Ascent for Regularized Loss Minimization. ICML Shai Shalev-Shwartz, Tong Zhang
2014	J	`jnl`	Accelerating Minibatch Stochastic Gradient Descent using Stratified Sampling. CoRR Peilin Zhao, Tong Zhang
2014	J	`jnl`	Adjusting Leverage Scores by Row Weighting: A Practical Approach to Coherent Matrix Completion. CoRR Shusen Wang, Tong Zhang, Zhihua Zhang
2014	A	`conf`	Batch-Mode Active Learning via Error Bound Minimization. UAI Quanquan Gu, Tong Zhang, Jiawei Han
2014	A*	`conf`	Communication-Efficient Distributed Optimization using an Approximate Newton-type Method. ICML Ohad Shamir, Nathan Srebro, Tong Zhang
2014	A*	`conf`	Compressed Counting Meets Compressed Sensing. COLT Ping Li, Cun-Hui Zhang, Tong Zhang
2014	J	`jnl`	Effective Use of Word Order for Text Categorization with Convolutional Neural Networks. CoRR Rie Johnson, Tong Zhang
2014	A*	`conf`	Efficient mini-batch training for stochastic optimization. KDD Mu Li, Tong Zhang, Yuqiang Chen, Alexander J. Smola
2014	A*	`conf`	Gradient Hard Thresholding Pursuit for Sparsity-Constrained Optimization. ICML Xiaotong Yuan, Ping Li, Tong Zhang
2014	A	`conf`	Gradient boosting factorization machines. RecSys Chen Cheng, Fen Xia, Tong Zhang, Irwin King, Michael R. Lyu
2014	J	`jnl`	Learning Nonlinear Functions Using Regularized Greedy Forest. IEEE Trans. Pattern Anal. Mach. Intell. Rie Johnson, Tong Zhang
2014	J	`jnl`	Partial Gaussian Graphical Model Estimation. IEEE Trans. Inf. Theory Xiao-Tong Yuan, Tong Zhang
2014	J	`jnl`	Pathwise Coordinate Optimization for Sparse Learning: Algorithm and Theory. CoRR Tuo Zhao, Han Liu, Tong Zhang
2014	J	`jnl`	Random Design Analysis of Ridge Regression. Found. Comput. Math. Daniel J. Hsu, Sham M. Kakade, Tong Zhang
2014	J	`jnl`	Randomized Dual Coordinate Ascent with Arbitrary Sampling. CoRR Zheng Qu, Peter Richtárik, Tong Zhang
2014	J	`jnl`	Sparse Recovery with Very Sparse Compressed Counting. CoRR Ping Li, Cun-Hui Zhang, Tong Zhang
2014	J	`jnl`	Stochastic Optimization with Importance Sampling. CoRR Peilin Zhao, Tong Zhang
2013	J	`jnl`	A Proximal-Gradient Homotopy Method for the Sparse Least-Squares Problem. SIAM J. Optim. Lin Xiao, Tong Zhang
2013	J	`jnl`	Accelerated Mini-Batch Stochastic Dual Coordinate Ascent CoRR Shai Shalev-Shwartz, Tong Zhang
2013	—	`conf`	Accelerated Mini-Batch Stochastic Dual Coordinate Ascent. NIPS Shai Shalev-Shwartz, Tong Zhang
2013	J	`jnl`	Accelerated Proximal Stochastic Dual Coordinate Ascent for Regularized Loss Minimization. CoRR Shai Shalev-Shwartz, Tong Zhang
2013	J	`jnl`	Accelerating Stochastic Alternating Direction Method of Multipliers with Adaptive Subgradient. CoRR Peilin Zhao, Jinwei Yang, Tong Zhang, Ping Li
2013	—	`conf`	Accelerating Stochastic Gradient Descent using Predictive Variance Reduction. NIPS Rie Johnson, Tong Zhang
2013	J	`jnl`	Aggregation of Affine Estimators. CoRR Dong Dai, Philippe Rigollet, Lucy Xia, Tong Zhang
2013	J	`jnl`	Communication Efficient Distributed Optimization using an Approximate Newton-type Method. CoRR Ohad Shamir, Nathan Srebro, Tong Zhang
2013	J	`jnl`	Compressed Counting Meets Compressed Sensing. CoRR Ping Li, Cun-Hui Zhang, Tong Zhang
2013	J	`jnl`	Gradient Hard Thresholding Pursuit for Sparsity-Constrained Optimization. CoRR Xiao-Tong Yuan, Ping Li, Tong Zhang
2013	A	`conf`	High-dimensional Joint Sparsity Random Effects Model for Multi-task Learning. UAI Krishnakumar Balasubramanian, Kai Yu, Tong Zhang
2013	J	`jnl`	High-dimensional Joint Sparsity Random Effects Model for Multi-task Learning. CoRR Krishnakumar Balasubramanian, Kai Yu, Tong Zhang
2013	—	`conf`	Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes. ICML (1) Ohad Shamir, Tong Zhang
2013	J	`jnl`	Stochastic dual coordinate ascent methods for regularized loss. J. Mach. Learn. Res. Shai Shalev-Shwartz, Tong Zhang
2013	J	`jnl`	Truncated power method for sparse eigenvalue problems. J. Mach. Learn. Res. Xiao-Tong Yuan, Tong Zhang
2012	A*	`conf`	A Proximal-Gradient Homotopy Method for the L1-Regularized Least-Squares Problem. ICML Lin Xiao, Tong Zhang
2012	J	`jnl`	A Proximal-Gradient Homotopy Method for the Sparse Least-Squares Problem CoRR Lin Xiao, Tong Zhang
2012	J	`jnl`	A spectral algorithm for learning Hidden Markov Models. J. Comput. Syst. Sci. Daniel J. Hsu, Sham M. Kakade, Tong Zhang
2012	J	`jnl`	Analysis of a randomized approximation scheme for matrix multiplication CoRR Daniel J. Hsu, Sham M. Kakade, Tong Zhang
2012	J	`jnl`	AntigenMap 3D: an online antigenic cartography resource. Bioinform. J. Lamar Barnett, Jialiang Yang, Zhipeng Cai, Tong Zhang, Xiu-Feng Wan
2012	J	`jnl`	Deviation Optimal Learning using Greedy Q-aggregation CoRR Dong Dai, Philippe Rigollet, Tong Zhang
2012	J	`jnl`	Learning Sparse Low-Threshold Linear Classifiers CoRR Sivan Sabato, Shai Shalev-Shwartz, Nathan Srebro, Daniel J. Hsu, Tong Zhang
2012	J	`jnl`	Partial Gaussian Graphical Model Estimation CoRR Xiao-Tong Yuan, Tong Zhang
2012	J	`jnl`	Proximal Stochastic Dual Coordinate Ascent CoRR Shai Shalev-Shwartz, Tong Zhang
2012	A*	`conf`	Random Design Analysis of Ridge Regression. COLT Daniel J. Hsu, Sham M. Kakade, Tong Zhang
2012	—	`conf`	Selective Labeling via Error Bound Minimization. NIPS Quanquan Gu, Tong Zhang, Chris H. Q. Ding, Jiawei Han
2012	J	`jnl`	Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization CoRR Shai Shalev-Shwartz, Tong Zhang
2012	J	`jnl`	Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes CoRR Ohad Shamir, Tong Zhang
2011	J	`jnl`	A tail inequality for quadratic forms of subgaussian random vectors CoRR Daniel J. Hsu, Sham M. Kakade, Tong Zhang
2011	J	`jnl`	Adaptive Forward-Backward Greedy Algorithm for Learning Sparse Representations. IEEE Trans. Inf. Theory Tong Zhang
2011	J	`jnl`	An Analysis of Random Design Linear Regression CoRR Daniel J. Hsu, Sham M. Kakade, Tong Zhang
2011	J	`jnl`	Dimension-free tail inequalities for sums of random matrices. CoRR Daniel J. Hsu, Sham M. Kakade, Tong Zhang
2011	J	`jnl`	Efficient Optimal Learning for Contextual Bandits CoRR Miroslav Dudík, Daniel J. Hsu, Satyen Kale, Nikos Karampatziakis, John Langford, Lev Reyzin, Tong Zhang
2011	A	`conf`	Efficient Optimal Learning for Contextual Bandits. UAI Miroslav Dudík, Daniel J. Hsu, Satyen Kale, Nikos Karampatziakis, John Langford, Lev Reyzin, Tong Zhang
2011	—	`conf`	Greedy Model Averaging. NIPS Dong Dai, Tong Zhang
2011	J	`jnl`	Integrative Analysis of Many Weighted Co-Expression Networks Using Tensor Computation. PLoS Comput. Biol. Wenyuan Li, Chun-Chi Liu, Tong Zhang, Haifeng Li, Michael S. Waterman, Xianghong Jasmine Zhou
2011	—	`conf`	Learning to Search Efficiently in High Dimensions. NIPS Zhen Li, Huazhong Ning, Liangliang Cao, Tong Zhang, Yihong Gong, Thomas S. Huang
2011	J	`jnl`	Learning with Structured Sparsity. J. Mach. Learn. Res. Junzhou Huang, Tong Zhang, Dimitris N. Metaxas
2011	J	`jnl`	Robust Matrix Decomposition With Sparse Corruptions. IEEE Trans. Inf. Theory Daniel J. Hsu, Sham M. Kakade, Tong Zhang
2011	J	`jnl`	Sparse Recovery With Orthogonal Matching Pursuit Under RIP. IEEE Trans. Inf. Theory Tong Zhang
2011	J	`jnl`	Spectral Methods for Learning Multivariate Latent Tree Structure CoRR Animashree Anandkumar, Kamalika Chaudhuri, Daniel J. Hsu, Sham M. Kakade, Le Song, Tong Zhang
2011	—	`conf`	Spectral Methods for Learning Multivariate Latent Tree Structure. NIPS Animashree Anandkumar, Kamalika Chaudhuri, Daniel J. Hsu, Sham M. Kakade, Le Song, Tong Zhang
2011	J	`jnl`	Truncated Power Method for Sparse Eigenvalue Problems CoRR Xiao-Tong Yuan, Tong Zhang
2010	J	`jnl`	A Computational Framework for Influenza Antigenic Cartography. PLoS Comput. Biol. Zhipeng Cai, Tong Zhang, Xiu-Feng Wan
2010	J	`jnl`	Agnostic Active Learning Without Constraints CoRR Alina Beygelzimer, Daniel J. Hsu, John Langford, Tong Zhang
2010	—	`conf`	Agnostic Active Learning Without Constraints. NIPS Alina Beygelzimer, Daniel J. Hsu, John Langford, Tong Zhang
2010	J	`jnl`	Analysis of Multi-stage Convex Relaxation for Sparse Regularization. J. Mach. Learn. Res. Tong Zhang
2010	—	`conf`	Deep Coding Network. NIPS Yuanqing Lin, Tong Zhang, Shenghuo Zhu, Kai Yu
2010	—	`ch.`	Fundamental Statistical Techniques. Handbook of Natural Language Processing Tong Zhang
2010	—	`book`	Fundamentals of Predictive Text Mining. Sholom M. Weiss, Nitin Indurkhya, Tong Zhang
2010	—	`conf`	Image Classification Using Super-Vector Coding of Local Image Descriptors. ECCV (5) Xi Zhou, Kai Yu, Tong Zhang, Thomas S. Huang
2010	A*	`conf`	Improved Local Coordinate Coding using Local Tangents. ICML Kai Yu, Tong Zhang
2010	J	`jnl`	Robust Matrix Decomposition with Outliers CoRR Daniel J. Hsu, Sham M. Kakade, Tong Zhang
2010	J	`jnl`	Sparse Recovery with Orthogonal Matching Pursuit under RIP CoRR Tong Zhang
2010	J	`jnl`	Trading Accuracy for Sparsity in Optimization Problems with Sparsity Constraints. SIAM J. Optim. Shai Shalev-Shwartz, Nathan Srebro, Tong Zhang
2009	A*	`conf`	A Spectral Algorithm for Learning Hidden Markov Models. COLT Daniel J. Hsu, Sham M. Kakade, Tong Zhang
2009	J	`jnl`	Classifying search queries using the Web as a source of knowledge. ACM Trans. Web Evgeniy Gabrilovich, Andrei Z. Broder, Marcus Fontoura, Amruta Joshi, Vanja Josifovski, Lance Riedel, Tong Zhang
2009	J	`jnl`	Learning Nonlinear Dynamic Models CoRR John Langford, Ruslan Salakhutdinov, Tong Zhang
2009	A*	`conf`	Learning nonlinear dynamic models. ICML John Langford, Ruslan Salakhutdinov, Tong Zhang
2009	A*	`conf`	Learning with structured sparsity. ICML Junzhou Huang, Tong Zhang, Dimitris N. Metaxas
2009	J	`jnl`	Multi-Label Prediction via Compressed Sensing CoRR Daniel J. Hsu, Sham M. Kakade, John Langford, Tong Zhang
2009	—	`conf`	Multi-Label Prediction via Compressed Sensing. NIPS Daniel J. Hsu, Sham M. Kakade, John Langford, Tong Zhang
2009	—	`conf`	Nonlinear Learning using Local Coordinate Coding. NIPS Kai Yu, Tong Zhang, Yihong Gong
2009	J	`jnl`	On the Consistency of Feature Selection using Greedy Least Squares Regression. J. Mach. Learn. Res. Tong Zhang
2009	J	`jnl`	Sparse Online Learning via Truncated Gradient. J. Mach. Learn. Res. John Langford, Lihong Li, Tong Zhang
2008	A*	`ed.`	21st Annual Conference on Learning Theory - COLT 2008, Helsinki, Finland, July 9-12, 2008 COLT Rocco A. Servedio, Tong Zhang
2008	J	`jnl`	A Spectral Algorithm for Learning Hidden Markov Models CoRR Daniel J. Hsu, Sham M. Kakade, Tong Zhang
2008	—	`conf`	Adaptive Forward-Backward Greedy Algorithm for Sparse Learning with Linear Models. NIPS Tong Zhang
2008	J	`jnl`	An Online Relevant Set Algorithm for Statistical Machine Translation. IEEE Trans. Speech Audio Process. Christoph Tillmann, Tong Zhang
2008	J	`jnl`	Graph-Based Semi-Supervised Learning and Spectral Kernel Design. IEEE Trans. Inf. Theory Rie Johnson, Tong Zhang
2008	—	`conf`	Multi-stage Convex Relaxation for Learning with Sparse Regularization. NIPS Tong Zhang
2008	J	`jnl`	Sparse Online Learning via Truncated Gradient CoRR John Langford, Lihong Li, Tong Zhang
2008	—	`conf`	Sparse Online Learning via Truncated Gradient. NIPS John Langford, Lihong Li, Tong Zhang
2008	J	`jnl`	Statistical Analysis of Bayes Optimal Subset Ranking. IEEE Trans. Inf. Theory David Cossock, Tong Zhang
2007	—	`conf`	A General Boosting Method and its Application to Learning Ranking Functions for Web Search. NIPS Zhaohui Zheng, Hongyuan Zha, Tong Zhang, Olivier Chapelle, Keke Chen, Gordon Sun
2007	J	`jnl`	A block bigram prediction model for statistical machine translation. ACM Trans. Speech Lang. Process. Christoph Tillmann, Tong Zhang
2007	A*	`conf`	Margin Based Active Learning. COLT Maria-Florina Balcan, Andrei Z. Broder, Tong Zhang
2007	J	`jnl`	On the Effectiveness of Laplacian Normalization for Graph Semi-supervised Learning. J. Mach. Learn. Res. Rie Johnson, Tong Zhang
2007	A*	`conf`	Robust classification of rare queries using web knowledge. SIGIR Andrei Z. Broder, Marcus Fontoura, Evgeniy Gabrilovich, Amruta Joshi, Vanja Josifovski, Tong Zhang
2007	—	`conf`	The Epoch-Greedy Algorithm for Multi-armed Bandits with Side Information. NIPS John Langford, Tong Zhang
2007	A*	`conf`	Two-view feature generation model for semi-supervised learning. ICML Rie Kubota Ando, Tong Zhang
2006	A*	`conf`	A Discriminative Global Training Algorithm for Statistical MT. ACL Christoph Tillmann, Tong Zhang
2006	—	`conf`	Effectiveness of Meeting Outcomes in Virtual vs. Face-to-Face Teams: A Comparison Study in China. AMCIS Zixiu Guo, John D'Ambra, Tim Turner, Huiying Zhang, Tong Zhang
2006	J	`jnl`	Information-theoretic upper and lower bounds for statistical estimation. IEEE Trans. Inf. Theory Tong Zhang
2006	—	`conf`	Learning on Graph with Laplacian Regularization. NIPS Rie Kubota Ando, Tong Zhang
2006	A*	`conf`	Linear prediction models with graph regularization for web-page categorization. KDD Tong Zhang, Alexandrin Popescul, Byron Dom
2006	A*	`conf`	Subset Ranking Using Regression. COLT David Cossock, Tong Zhang
2005	J	`jnl`	A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data. J. Mach. Learn. Res. Rie Kubota Ando, Tong Zhang
2005	A*	`conf`	A High-Performance Semi-Supervised Learning Method for Text Chunking. ACL Rie Kubota Ando, Tong Zhang
2005	A*	`conf`	A Localized Prediction Model for Statistical Machine Translation. ACL Christoph Tillmann, Tong Zhang
2005	—	`conf`	Analysis of Spectral Kernel Design based Semi-supervised Learning. NIPS Tong Zhang, Rie Kubota Ando
2005	A*	`conf`	Data Dependent Concentration Bounds for Sequential Prediction Algorithms. COLT Tong Zhang
2005	J	`jnl`	Learning Bounds for Kernel Regression Using Effective Data Dimensionality. Neural Comput. Tong Zhang
2005	A*	`conf`	Localized Upper and Lower Bounds for Some Estimation Problems. COLT Tong Zhang
2005	—	`conf`	TREC 2005 Genomics Track Experiments at IBM Watson. TREC Rie Kubota Ando, Mark Dredze, Tong Zhang
2004	B	`conf`	Chinese Named Entity Recognition Based on Multilevel Linguistic Features. IJCNLP Honglei Guo, Jianmin Jiang, Gang Hu, Tong Zhang
2004	—	`conf`	Class-size Independent Generalization Analsysis of Some Discriminative Multi-Category Classification. NIPS Tong Zhang
2004	A*	`conf`	Column-generation boosting methods for mixture of kernels. KDD Jinbo Bi, Tong Zhang, Kristin P. Bennett
2004	A*	`conf`	Focused named entity recognition using machine learning. SIGIR Li Zhang, Yue Pan, Tong Zhang
2004	A*	`conf`	On the Convergence of MDL Density Estimation. COLT Tong Zhang
2004	A*	`conf`	Solving large scale linear prediction problems using stochastic gradient descent algorithms. ICML Tong Zhang
2004	J	`jnl`	Statistical Analysis of Some Multi-Category Large Margin Classification Methods. J. Mach. Learn. Res. Tong Zhang
2004	—	`conf`	Support Vector Classification with Input Data Uncertainty. NIPS Jinbo Bi, Tong Zhang
2004	J	`jnl`	Text categorization for a comprehensive time-dependent benchmark. Inf. Process. Manag. Fred Damerau, Tong Zhang, Sholom M. Weiss, Nitin Indurkhya
2003	B	`conf`	A Robust Risk Minimization based Named Entity Recognition System. CoNLL Tong Zhang, David Johnson
2003	—	`conf`	An Infinity-sample Theory for Multi-category Large Margin Classification. NIPS Tong Zhang
2003	J	`jnl`	Generalization Error Bounds for Bayesian Mixture Algorithms. J. Mach. Learn. Res. Ron Meir, Tong Zhang
2003	J	`jnl`	Greedy Algorithms for Classification -- Consistency, Convergence Rates, and Adaptivity. J. Mach. Learn. Res. Shie Mannor, Ron Meir, Tong Zhang
2003	A*	`conf`	HowtogetaChineseName(Entity): Segmentation and Combination Issues. EMNLP Hongyan Jing, Radu Florian, Xiaoqiang Luo, Tong Zhang, Abraham Ittycheriah
2003	—	`conf`	Learning Bounds for a Generalized Family of Bayesian Posterior Distributions. NIPS Tong Zhang
2003	J	`jnl`	Leave-One-Out Bounds for Kernel Methods. Neural Comput. Tong Zhang
2003	B	`conf`	Named Entity Recognition through Classifier Combination. CoNLL Radu Florian, Abraham Ittycheriah, Hongyan Jing, Tong Zhang
2003	A*	`conf`	On the Convergence of Boosting Procedures. ICML Tong Zhang, Bin Yu
2003	J	`jnl`	Sequential greedy approximation for certain convex optimization problems. IEEE Trans. Inf. Theory Tong Zhang
2003	B	`conf`	Updating an NLP system to fit new domains: an empirical study on the sentence segmentation problem. CoNLL Tong Zhang, Fred Damerau, David Johnson
2002	J	`jnl`	A decision-tree-based symbolic rule induction system for text categorization. IBM Syst. J. David E. Johnson, Frank J. Oles, Tong Zhang, Thilo Götz
2002	J	`jnl`	Approximation Bounds for Some Sparse Kernel Regression Algorithms. Neural Comput. Tong Zhang
2002	J	`jnl`	Covering Number Bounds of Certain Regularized Linear Function Classes. J. Mach. Learn. Res. Tong Zhang
2002	—	`conf`	Data-Dependent Bounds for Bayesian Mixture Methods. NIPS Ron Meir, Tong Zhang
2002	—	`conf`	Effective Dimension and Generalization of Kernel Learning. NIPS Tong Zhang
2002	A*	`conf`	Experiments in high-dimensional text categorization. SIGIR Fred Damerau, Tong Zhang, Sholom M. Weiss, Nitin Indurkhya
2002	J	`jnl`	On the Consistency of Instantaneous Rigid Motion Estimation. Int. J. Comput. Vis. Tong Zhang, Carlo Tomasi
2002	J	`jnl`	On the Dual Formulation of Regularized Linear Systems with Convex Risks. Mach. Learn. Tong Zhang
2002	J	`jnl`	Recommender Systems Using Linear Classifier. J. Mach. Learn. Res. Tong Zhang, Vijay S. Iyengar
2002	A*	`conf`	Statistical Behavior and Consistency of Support Vector Machines, Boosting, and Beyond. ICML Tong Zhang
2002	J	`jnl`	Text Chunking based on a Generalization of Winnow. J. Mach. Learn. Res. Tong Zhang, Fred Damerau, David Johnson
2002	A*	`conf`	The Consistency of Greedy Algorithms for Classification. COLT Shie Mannor, Ron Meir, Tong Zhang
2002	J	`jnl`	Two-Sided Arnoldi and Nonsymmetric Lanczos Algorithms. SIAM J. Matrix Anal. Appl. Jane Cullum, Tong Zhang
2001	—	`conf`	A General Greedy Approximation Algorithm with Applications. NIPS Tong Zhang
2001	—	`conf`	A Leave-One-out Cross Validation Bound for Kernel Methods with Applications in Learning. COLT/EuroCOLT Tong Zhang
2001	—	`conf`	A Sequential Approximation Bound for Some Sample-Dependent Convex Optimization Problems with Applications in Learning. COLT/EuroCOLT Tong Zhang
2001	J	`jnl`	An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods. AI Mag. Tong Zhang
2001	B	`conf`	Empirical Study of Recommender Systems Using Linear Classifiers. PAKDD Vijay S. Iyengar, Tong Zhang
2001	—	`conf`	Generalization Performance of Some Learning Problems in Hilbert Functional Spaces. NIPS Tong Zhang
2001	J	`jnl`	Rank-One Approximation to High Order Tensors. SIAM J. Matrix Anal. Appl. Tong Zhang, Gene H. Golub
2001	A*	`conf`	Some Sparse Approximation Bounds for Regression Problems. ICML Tong Zhang
2001	J	`jnl`	Text Categorization Based on Regularized Linear Classification Methods. Inf. Retr. Tong Zhang, Frank J. Oles
2001	A*	`conf`	Text Chunking using Regularized Winnow. ACL Tong Zhang, Fred Damerau, David Johnson
2000	A*	`conf`	Active learning using adaptive resampling. KDD Vijay S. Iyengar, Chidanand Apté, Tong Zhang
2000	—	`conf`	Convergence of Large Margin Separable Linear Classification. NIPS Tong Zhang
2000	—	`conf`	Regularized Winnow Methods. NIPS Tong Zhang
1999	A*	`conf`	Fast, Robust, and Consistent Camera Motion Estimation. CVPR Tong Zhang, Carlo Tomasi
1999	—	`conf`	Some Theoretical Results Concerning the Convergence of Compositions of Regularized Linear Functions. NIPS Tong Zhang
1999	A*	`conf`	Theoretical Analysis of a Class of Randomized Regularization Methods. COLT Tong Zhang
1998	—	`conf`	A Linear Algorithm for Optimal Context Clustering with Application to Bi-level Image Coding. ICIP (1) Daniel H. Greene, F. Frances Yao, Tong Zhang
1998	B	`conf`	Compression by Model Combination. Data Compression Conference Tong Zhang
1998	—	`—`	Methods for computational and statistical estimation with applications. Tong Zhang
1998	J	`jnl`	On the Homotopy Method for Perturbed Symmetric Generalized Eigenvalue Problems. SIAM J. Sci. Comput. Tong Zhang, Kincho H. Law, Gene H. Golub
1997	—	`conf`	A progressive Ziv-Lempel algorithm for image compression. SEQUENCES Daniel Greene, Mohan Vishwanath, F. Frances Yao, Tong Zhang
1996	—	`conf`	Optimal Surface Smoothing as Filter Design. ECCV (1) Gabriel Taubin, Tong Zhang, Gene H. Golub
1995	J	`jnl`	Densities of Self-Similar Measures on the Line. Exp. Math. Robert S. Strichartz, Arthur Taylor, Tong Zhang