Cho-Jui Hsieh - RankMe

481 papers A* 148A 15B 3C 1Journal 258Unranked 56

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	AI Co-Scientist for Ranking: Discovering Novel Search Ranking Models alongside LLM-based AI Agents with Cloud Computing Access. CoRR Liwei Wu, Cho-Jui Hsieh
2026	J	`jnl`	FastLane: Efficient Routed Systems for Late-Interaction Retrieval. CoRR Ramnath Kumar, Prateek Jain, Cho-Jui Hsieh
2026	J	`jnl`	FlexAct: Why Learn when you can Pick? CoRR Ramnath Kumar, Kyle Ritscher, Junmin Judy, Lawrence Liu, Cho-Jui Hsieh
2026	J	`jnl`	Generalized Transferable Attack Across Datasets. IEEE Trans. Circuits Syst. Video Technol. Yunxiao Qin, Yuanhao Xiong, Jinfeng Yi, Lihong Cao, Cho-Jui Hsieh
2026	J	`jnl`	LoL: Longer than Longer, Scaling Video Generation to Hour. CoRR Justin Cui, Jie Wu, Ming Li, Tao Yang, Xiaojie Li, Rui Wang, Andrew Bai, Yuanhao Ban, Cho-Jui Hsieh
2026	J	`jnl`	Text is All You Need for Vision-Language Model Jailbreaking. CoRR Yihang Chen, Zhao Xu, Youyuan Jiang, Tianle Zheng, Cho-Jui Hsieh
2026	J	`jnl`	Understanding Reward Hacking in Text-to-Image Reinforcement Learning. CoRR Yunqi Hong, Kuei-Chun Kao, Hengguang Zhou, Cho-Jui Hsieh
2025	J	`jnl`	Adaptive Diagnostic Reasoning Framework for Pathology with Multimodal Large Language Models. CoRR Yunqi Hong, Johnson Kao, Liam Edwards, Nein-Tzu Liu, Chung-Yen Huang, Alex Oliveira-Kowaleski, Cho-Jui Hsieh, Neil Y. C. Lin
2025	—	`conf`	An Efficient Rehearsal Scheme for Catastrophic Forgetting Mitigation during Multi-stage Fine-tuning. NAACL (Findings) Andrew Bai, Chih-Kuan Yeh, Cho-Jui Hsieh, Ankur Taly
2025	J	`jnl`	Compressing Many-Shots in In-Context Learning. CoRR Devvrit Khatri, Pranamya Kulkarni, Nilesh Gupta, Yerram Varun, Liqian Peng, Jay Yagnik, Praneeth Netrapalli, Cho-Jui Hsieh, Alec Go, Inderjit S. Dhillon, Aditya Kusupati, Prateek Jain
2025	J	`jnl`	Concepts or Skills? Rethinking Instruction Selection for Multi-modal Models. CoRR Andrew Bai, Justin Cui, Ruochen Wang, Cho-Jui Hsieh
2025	J	`jnl`	DialectGen: Benchmarking and Improving Dialect Robustness in Multimodal Generation. CoRR Yu Zhou, Sohyun An, Haikang Deng, Da Yin, Clark Peng, Cho-Jui Hsieh, Kai-Wei Chang, Nanyun Peng
2025	J	`jnl`	Don't Think Longer, Think Wisely: Optimizing Thinking Dynamics for Large Reasoning Models. CoRR Sohyun An, Ruochen Wang, Tianyi Zhou, Cho-Jui Hsieh
2025	J	`jnl`	Exploring Expert Failures Improves LLM Agent Tuning. CoRR Li-Cheng Lan, Andrew Bai, Minhao Cheng, Cho-Jui Hsieh, Tianyi Zhou
2025	J	`jnl`	IRIS: Intrinsic Reward Image Synthesis. CoRR Yihang Chen, Yuanhao Ban, Yunqi Hong, Cho-Jui Hsieh
2025	A*	`conf`	Is Your Multimodal Language Model Oversensitive to Safe Queries? ICLR Xirui Li, Hengguang Zhou, Ruochen Wang, Tianyi Zhou, Minhao Cheng, Cho-Jui Hsieh
2025	J	`jnl`	LLM-guided Hierarchical Retrieval. CoRR Nilesh Gupta, Wei-Cheng Chang, Ngot Bui, Cho-Jui Hsieh, Inderjit S. Dhillon
2025	A*	`conf`	Large Language Models are Interpretable Learners. ICLR Ruochen Wang, Si Si, Felix X. Yu, Dorothea Wiesmann Rothuizen, Cho-Jui Hsieh, Inderjit S. Dhillon
2025	A*	`conf`	LoRA Done RITE: Robust Invariant Transformation Equilibration for LoRA Optimization. ICLR Jui-Nan Yen, Si Si, Zhao Meng, Felix X. Yu, Sai Surya Duvvuri, Inderjit S. Dhillon, Cho-Jui Hsieh, Sanjiv Kumar
2025	—	`conf`	Matryoshka Model Learning for Improved Elastic Student Models. KDD (2) Chetan Verma, Aditya Srinivas Timmaraju, Cho-Jui Hsieh, Suyash Damle, Ngot Bui, Yang Zhang, Wen Chen, Xin Liu, Prateek Jain, Inderjit S. Dhillon
2025	J	`jnl`	Matryoshka Model Learning for Improved Elastic Student Models. CoRR Chetan Verma, Aditya Srinivas Timmaraju, Cho-Jui Hsieh, Suyash Damle, Ngot Bui, Yang Zhang, Wen Chen, Xin Liu, Prateek Jain, Inderjit S. Dhillon
2025	—	`conf`	Neural Network Verification with Branch-and-Bound for General Nonlinearities. TACAS (1) Zhouxing Shi, Qirui Jin, Zico Kolter, Suman Jana, Cho-Jui Hsieh, Huan Zhang
2025	A*	`conf`	OR-Bench: An Over-Refusal Benchmark for Large Language Models. ICML Justin Cui, Wei-Lin Chiang, Ion Stoica, Cho-Jui Hsieh
2025	J	`jnl`	POME: Post Optimization Model Edit via Muon-style Projection. CoRR Yong Liu, Di Fu, Yang Luo, Zirui Zhu, Minhao Cheng, Cho-Jui Hsieh, Yang You
2025	J	`jnl`	Provably Robust Training of Quantum Circuit Classifiers Against Parameter Noise. CoRR Lucas Tecot, Di Luo, Cho-Jui Hsieh
2025	A*	`conf`	QG-CoC: Question-Guided Chain-of-Captions for Large Multimodal Models. EMNLP Kuei-Chun Kao, Hsu Tzu-Yin, Yunqi Hong, Ruochen Wang, Cho-Jui Hsieh
2025	J	`jnl`	QG-CoC: Question-Guided Chain-of-Captions for Large Multimodal Models. CoRR Kuei-Chun Kao, Hsu Tzu-Yin, Yunqi Hong, Ruochen Wang, Cho-Jui Hsieh
2025	J	`jnl`	R1-Zero's "Aha Moment" in Visual Reasoning on a 2B Non-SFT Model. CoRR Hengguang Zhou, Xirui Li, Ruochen Wang, Minhao Cheng, Tianyi Zhou, Cho-Jui Hsieh
2025	J	`jnl`	Rethinking RL Evaluation: Can Benchmarks Truly Reveal Failures of RL Methods? CoRR Zihan Chen, Yiming Zhang, Hengguang Zhou, Zenghui Ding, Yining Sun, Cho-Jui Hsieh
2025	A*	`conf`	SeedLoRA: A Fusion Approach to Efficient LLM Fine-Tuning. ICML Yong Liu, Di Fu, Shenggan Cheng, Zirui Zhu, Yang Luo, Minhao Cheng, Cho-Jui Hsieh, Yang You
2025	J	`jnl`	Self-Forcing++: Towards Minute-Scale High-Quality Video Generation. CoRR Justin Cui, Jie Wu, Ming Li, Tao Yang, Xiaojie Li, Rui Wang, Andrew Bai, Yuanhao Ban, Cho-Jui Hsieh
2025	J	`jnl`	SoundnessBench: A Soundness Benchmark for Neural Network Verifiers. Trans. Mach. Learn. Res. Xingjian Zhou, Keyi Shen, Andy Xu, Hongji Xu, Cho-Jui Hsieh, Huan Zhang, Zhouxing Shi
2025	J	`jnl`	Stochastic Optimization for Nonconvex Problem With Inexact Hessian Matrix, Gradient, and Function. IEEE Trans. Neural Networks Learn. Syst. Liu Liu, Xuanqing Liu, Cho-Jui Hsieh, Dacheng Tao
2025	A*	`conf`	The Crystal Ball Hypothesis in diffusion models: Anticipating object positions from initial noise. ICLR Yuanhao Ban, Ruochen Wang, Tianyi Zhou, Boqing Gong, Cho-Jui Hsieh, Minhao Cheng
2025	J	`jnl`	Uncertainty-Guided Selective Adaptation Enables Cross-Platform Predictive Fluorescence Microscopy. CoRR Kai-Wen K. Yang, Andrew Bai, Alexandra Bermudez, Yunqi Hong, Zoe Latham, Iris Sloan, Michael Liu, Vishrut Goyal, Cho-Jui Hsieh, Neil Y. C. Lin
2025	A*	`conf`	UniDEC : Unified Dual Encoder and Classifier Training for Extreme Multi-Label Classification. WWW Siddhant Kharbanda, Devaansh Gupta, Gururaj K, Pankaj Malhotra, Amit Singh, Cho-Jui Hsieh, Rohit Babbar
2025	J	`jnl`	Unlabeled Data Improves Fine-Grained Image Zero-shot Classification with Multimodal LLMs. CoRR Yunqi Hong, Sohyun An, Andrew Bai, Neil Y. C. Lin, Cho-Jui Hsieh
2025	J	`jnl`	When Distance Distracts: Representation Distance Bias in BT-Loss for Reward Models. CoRR Tong Xie, Andrew Bai, Yuanhao Ban, Yunqi Hong, Haoyu Li, Cho-Jui Hsieh
2024	J	`jnl`	Accelerating Large Language Model Pretraining via LFR Pedagogy: Learn, Focus, and Review. CoRR Neha Prakriya, Jui-Nan Yen, Cho-Jui Hsieh, Jason Cong
2024	J	`jnl`	Adversarial Examples Detection With Bayesian Neural Network. IEEE Trans. Emerg. Top. Comput. Intell. Yao Li, Tongyi Tang, Cho-Jui Hsieh, Thomas C. M. Lee
2024	A*	`conf`	Ameliorate Spurious Correlations in Dataset Condensation. ICML Justin Cui, Ruochen Wang, Yuanhao Xiong, Cho-Jui Hsieh
2024	J	`jnl`	Ameliorate Spurious Correlations in Dataset Condensation. CoRR Justin Cui, Ruochen Wang, Yuanhao Xiong, Cho-Jui Hsieh
2024	—	`conf`	Automatic Engineering of Long Prompts. ACL (Findings) Cho-Jui Hsieh, Si Si, Felix X. Yu, Inderjit S. Dhillon
2024	J	`jnl`	CLUE: Concept-Level Uncertainty Estimation for Large Language Models. CoRR Yu-Hsiang Wang, Andrew Bai, Che-Ping Tsai, Cho-Jui Hsieh
2024	J	`jnl`	Certified Training with Branch-and-Bound: A Case Study on Lyapunov-stable Neural Control. CoRR Zhouxing Shi, Cho-Jui Hsieh, Huan Zhang
2024	A*	`conf`	Combining Axes Preconditioners through Kronecker Approximation for Deep Learning. ICLR Sai Surya Duvvuri, Devvrit, Rohan Anil, Cho-Jui Hsieh, Inderjit S. Dhillon
2024	J	`jnl`	Data Attribution for Diffusion Models: Timestep-induced Bias in Influence Estimation. CoRR Tong Xie, Haoyu Li, Andrew Bai, Cho-Jui Hsieh
2024	J	`jnl`	Data Attribution for Diffusion Models: Timestep-induced Bias in Influence Estimation. Trans. Mach. Learn. Res. Tong Xie, Haoyu Li, Andrew Bai, Cho-Jui Hsieh
2024	—	`conf`	Defending LLMs against Jailbreaking Attacks via Backtranslation. ACL (Findings) Yihan Wang, Zhouxing Shi, Andrew Bai, Cho-Jui Hsieh
2024	J	`jnl`	Defending LLMs against Jailbreaking Attacks via Backtranslation. CoRR Yihan Wang, Zhouxing Shi, Andrew Bai, Cho-Jui Hsieh
2024	J	`jnl`	DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers. CoRR Xirui Li, Ruochen Wang, Minhao Cheng, Tianyi Zhou, Cho-Jui Hsieh
2024	—	`conf`	DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLMs Jailbreakers. EMNLP (Findings) Xirui Li, Ruochen Wang, Minhao Cheng, Tianyi Zhou, Cho-Jui Hsieh
2024	J	`jnl`	Efficient Frameworks for Generalized Low-Rank Matrix Bandit Problems. CoRR Yue Kang, Cho-Jui Hsieh, Thomas C. M. Lee
2024	J	`jnl`	Embedding Space Selection for Detecting Memorization and Fingerprinting in Generative Models. CoRR Jack He, Jianxing Zhao, Andrew Bai, Cho-Jui Hsieh
2024	A*	`conf`	Entity Disambiguation with Extreme Multi-label Ranking. WWW Jyun-Yu Jiang, Wei-Cheng Chang, Jiong Zhang, Cho-Jui Hsieh, Hsiang-Fu Yu
2024	A*	`conf`	Expert Proximity as Surrogate Rewards for Single Demonstration Imitation Learning. ICML Chia-Cheng Chiang, Li-Cheng Lan, Wei-Fang Sun, Chien Feng, Cho-Jui Hsieh, Chun-Yi Lee
2024	J	`jnl`	Expert Proximity as Surrogate Rewards for Single Demonstration Imitation Learning. CoRR Chia-Cheng Chiang, Li-Cheng Lan, Wei-Fang Sun, Chien Feng, Cho-Jui Hsieh, Chun-Yi Lee
2024	A*	`conf`	Gandalf: Learning Label-label Correlations in Extreme Multi-label Classification via Label Features. KDD Siddhant Kharbanda, Devaansh Gupta, Erik Schultheis, Atmadeep Banerjee, Cho-Jui Hsieh, Rohit Babbar
2024	J	`jnl`	JIGMARK: A Black-Box Approach for Enhancing Image Watermarks against Diffusion Model Edits. CoRR Minzhou Pan, Yi Zeng, Xue Lin, Ning Yu, Cho-Jui Hsieh, Peter Henderson, Ruoxi Jia
2024	J	`jnl`	Large Language Models are Interpretable Learners. CoRR Ruochen Wang, Si Si, Felix X. Yu, Dorothea Wiesmann, Cho-Jui Hsieh, Inderjit S. Dhillon
2024	J	`jnl`	Learning label-label correlations in Extreme Multi-label Classification via Label Features. CoRR Siddhant Kharbanda, Devaansh Gupta, Erik Schultheis, Atmadeep Banerjee, Cho-Jui Hsieh, Rohit Babbar
2024	J	`jnl`	LoRA Done RITE: Robust Invariant Transformation Equilibration for LoRA Optimization. CoRR Jui-Nan Yen, Si Si, Zhao Meng, Felix X. Yu, Sai Surya Duvvuri, Inderjit S. Dhillon, Cho-Jui Hsieh, Sanjiv Kumar
2024	A	`conf`	Low-rank Matrix Bandits with Heavy-tailed Rewards. UAI Yue Kang, Cho-Jui Hsieh, Thomas Chun Man Lee
2024	J	`jnl`	Low-rank Matrix Bandits with Heavy-tailed Rewards. CoRR Yue Kang, Cho-Jui Hsieh, Thomas C. M. Lee
2024	J	`jnl`	Lyapunov-stable Neural Control for State and Output Feedback: A Novel Formulation for Efficient Synthesis and Verification. CoRR Lujie Yang, Hongkai Dai, Zhouxing Shi, Cho-Jui Hsieh, Russ Tedrake, Huan Zhang
2024	A*	`conf`	Lyapunov-stable Neural Control for State and Output Feedback: A Novel Formulation. ICML Lujie Yang, Hongkai Dai, Zhouxing Shi, Cho-Jui Hsieh, Russ Tedrake, Huan Zhang
2024	J	`jnl`	MOSSBench: Is Your Multimodal Language Model Oversensitive to Safe Queries? CoRR Xirui Li, Hengguang Zhou, Ruochen Wang, Tianyi Zhou, Minhao Cheng, Cho-Jui Hsieh
2024	—	`conf`	MinPrompt: Graph-based Minimal Prompt Data Augmentation for Few-shot Question Answering. ACL (1) Xiusi Chen, Jyun-Yu Jiang, Wei-Cheng Chang, Cho-Jui Hsieh, Hsiang-Fu Yu, Wei Wang
2024	J	`jnl`	MuLan: Multimodal-LLM Agent for Progressive Multi-Object Diffusion. CoRR Sen Li, Ruochen Wang, Cho-Jui Hsieh, Minhao Cheng, Tianyi Zhou
2024	J	`jnl`	Neural Network Verification with Branch-and-Bound for General Nonlinearities. CoRR Zhouxing Shi, Qirui Jin, Zico Kolter, Suman Jana, Cho-Jui Hsieh, Huan Zhang
2024	J	`jnl`	OR-Bench: An Over-Refusal Benchmark for Large Language Models. CoRR Justin Cui, Wei-Lin Chiang, Ion Stoica, Cho-Jui Hsieh
2024	A*	`conf`	On Discrete Prompt Optimization for Diffusion Models. ICML Ruochen Wang, Ting Liu, Cho-Jui Hsieh, Boqing Gong
2024	J	`jnl`	On Discrete Prompt Optimization for Diffusion Models. CoRR Ruochen Wang, Ting Liu, Cho-Jui Hsieh, Boqing Gong
2024	J	`jnl`	On the loss of context-awareness in general instruction fine-tuning. CoRR Yihan Wang, Andrew Bai, Nanyun Peng, Cho-Jui Hsieh
2024	A*	`conf`	One Prompt is not Enough: Automated Construction of a Mixture-of-Expert Prompts. ICML Ruochen Wang, Sohyun An, Minhao Cheng, Tianyi Zhou, Sung Ju Hwang, Cho-Jui Hsieh
2024	J	`jnl`	One Prompt is not Enough: Automated Construction of a Mixture-of-Expert Prompts. CoRR Ruochen Wang, Sohyun An, Minhao Cheng, Tianyi Zhou, Sung Ju Hwang, Cho-Jui Hsieh
2024	J	`jnl`	Online Continuous Hyperparameter Optimization for Generalized Linear Contextual Bandits. Trans. Mach. Learn. Res. Yue Kang, Cho-Jui Hsieh, Thomas C. M. Lee
2024	A	`conf`	PEFA: Parameter-Free Adapters for Large-scale Embedding-based Retrieval Models. WSDM Wei-Cheng Chang, Jyun-Yu Jiang, Jiong Zhang, Mutasem Al-Darabsah, Choon Hui Teo, Cho-Jui Hsieh, Hsiang-Fu Yu, S. V. N. Vishwanathan
2024	—	`conf`	Randomized Benchmarking of Local Zeroth-Order Optimizers for Variational Quantum Systems. TPS-ISA Lucas Tecot, Cho-Jui Hsieh
2024	J	`jnl`	Red Teaming Language Model Detectors with Language Models. Trans. Assoc. Comput. Linguistics Zhouxing Shi, Yihan Wang, Fan Yin, Xiangning Chen, Kai-Wei Chang, Cho-Jui Hsieh
2024	—	`conf`	Solving for X and Beyond: Can Large Language Models Solve Complex Math Problems with More-Than-Two Unknowns? EMNLP (Findings) Kuei-Chun Kao, Ruochen Wang, Cho-Jui Hsieh
2024	J	`jnl`	Solving for X and Beyond: Can Large Language Models Solve Complex Math Problems with More-Than-Two Unknowns? CoRR Kuei-Chun Kao, Ruochen Wang, Cho-Jui Hsieh
2024	J	`jnl`	Sparse MeZO: Less Parameters for Better Performance in Zeroth-Order LLM Fine-Tuning. CoRR Yong Liu, Zirui Zhu, Chaoyu Gong, Minhao Cheng, Cho-Jui Hsieh, Yang You
2024	A*	`conf`	Structured Video-Language Modeling with Temporal Grouping and Spatial Grounding. ICLR Yuanhao Xiong, Long Zhao, Boqing Gong, Ming-Hsuan Yang, Florian Schroff, Ting Liu, Cho-Jui Hsieh, Liangzhe Yuan
2024	J	`jnl`	Temporal shuffling for defending deep action recognition models against adversarial attacks. Neural Networks Jaehui Hwang, Huan Zhang, Jun-Ho Choi, Cho-Jui Hsieh, Jong-Seok Lee
2024	J	`jnl`	Testing Neural Network Verifiers: A Soundness Benchmark with Hidden Counterexamples. CoRR Xingjian Zhou, Hongji Xu, Andy Xu, Zhouxing Shi, Cho-Jui Hsieh, Huan Zhang
2024	J	`jnl`	The Crystal Ball Hypothesis in diffusion models: Anticipating object positions from initial noise. CoRR Yuanhao Ban, Ruochen Wang, Tianyi Zhou, Boqing Gong, Cho-Jui Hsieh, Minhao Cheng
2024	A*	`conf`	Two-stage LLM Fine-tuning with Less Specialization and More Generalization. ICLR Yihan Wang, Si Si, Daliang Li, Michal Lukasik, Felix X. Yu, Cho-Jui Hsieh, Inderjit S. Dhillon, Sanjiv Kumar
2024	A*	`conf`	UNICORN: A Unified Causal Video-Oriented Language-Modeling Framework for Temporal Video-Language Tasks. EMNLP Yuanhao Xiong, Yixin Nie, Haotian Liu, Boxin Wang, Jun Chen, Rong Jin, Cho-Jui Hsieh, Lorenzo Torresani, Jie Lei
2024	J	`jnl`	Uncovering Distortion Differences: A Study of Adversarial Attacks and Machine Discriminability. IEEE Access Xiawei Wang, Yao Li, Cho-Jui Hsieh, Thomas C. M. Lee
2024	—	`conf`	Understanding the Impact of Negative Prompts: When and How Do They Take Effect? ECCV (89) Yuanhao Ban, Ruochen Wang, Tianyi Zhou, Minhao Cheng, Boqing Gong, Cho-Jui Hsieh
2024	J	`jnl`	Understanding the Impact of Negative Prompts: When and How Do They Take Effect? CoRR Yuanhao Ban, Ruochen Wang, Tianyi Zhou, Minhao Cheng, Boqing Gong, Cho-Jui Hsieh
2024	J	`jnl`	UniDEC : Unified Dual Encoder and Classifier Training for Extreme Multi-Label Classification. CoRR Siddhant Kharbanda, Devaansh Gupta, Gururaj K, Pankaj Malhotra, Cho-Jui Hsieh, Rohit Babbar
2024	J	`jnl`	Which Pretrain Samples to Rehearse when Finetuning Pretrained Models? CoRR Andrew Bai, Chih-Kuan Yeh, Cho-Jui Hsieh, Ankur Taly
2023	A*	`conf`	A Computationally Efficient Sparsified Online Newton Method. NeurIPS Devvrit, Sai Surya Duvvuri, Rohan Anil, Vineet Gupta, Cho-Jui Hsieh, Inderjit S. Dhillon
2023	J	`jnl`	A Computationally Efficient Sparsified Online Newton Method. CoRR Devvrit, Sai Surya Duvvuri, Rohan Anil, Vineet Gupta, Cho-Jui Hsieh, Inderjit S. Dhillon
2023	J	`jnl`	Automatic Engineering of Long Prompts. CoRR Cho-Jui Hsieh, Si Si, Felix X. Yu, Inderjit S. Dhillon
2023	A*	`conf`	Block Low-Rank Preconditioner with Shared Basis for Stochastic Optimization. NeurIPS Jui-Nan Yen, Sai Surya Duvvuri, Inderjit S. Dhillon, Cho-Jui Hsieh
2023	A	`conf`	Build Faster with Less: A Journey to Accelerate Sparse Model Building for Semantic Matching in Product Search. CIKM Jiong Zhang, Yau-Shian Wang, Wei-Cheng Chang, Wei Li, Jyun-Yu Jiang, Cho-Jui Hsieh, Hsiang-Fu Yu
2023	A*	`conf`	Can Agents Run Relay Race with Strangers? Generalization of RL to Out-of-Distribution Trajectories. ICLR Li-Cheng Lan, Huan Zhang, Cho-Jui Hsieh
2023	J	`jnl`	Can Agents Run Relay Race with Strangers? Generalization of RL to Out-of-Distribution Trajectories. CoRR Li-Cheng Lan, Huan Zhang, Cho-Jui Hsieh
2023	A*	`conf`	Concept Gradient: Concept-based Interpretation Without Linear Assumption. ICLR Andrew Bai, Chih-Kuan Yeh, Neil Y. C. Lin, Pradeep Kumar Ravikumar, Cho-Jui Hsieh
2023	A*	`conf`	Effective Robustness against Natural Distribution Shifts for Models with Different Training Data. NeurIPS Zhouxing Shi, Nicholas Carlini, Ananth Balashankar, Ludwig Schmidt, Cho-Jui Hsieh, Alex Beutel, Yao Qin
2023	J	`jnl`	Effective Robustness against Natural Distribution Shifts for Models with Different Training Data. CoRR Zhouxing Shi, Nicholas Carlini, Ananth Balashankar, Ludwig Schmidt, Cho-Jui Hsieh, Alex Beutel, Yao Qin
2023	—	`conf`	Enhancing Unsupervised Semantic Parsing with Distributed Contextual Representations. ACL (Findings) Zixuan Ling, Xiaoqing Zheng, Jianhan Xu, Jinshu Lin, Kai-Wei Chang, Cho-Jui Hsieh, Xuanjing Huang
2023	A*	`conf`	FINGER: Fast Inference for Graph-based Approximate Nearest Neighbor Search. WWW Patrick H. Chen, Wei-Cheng Chang, Jyun-Yu Jiang, Hsiang-Fu Yu, Inderjit S. Dhillon, Cho-Jui Hsieh
2023	J	`jnl`	Fast block-wise partitioning for extreme multi-label classification. Data Min. Knowl. Discov. Yuefeng Liang, Cho-Jui Hsieh, Thomas C. M. Lee
2023	A*	`conf`	FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning. CVPR Yuanhao Xiong, Ruochen Wang, Minhao Cheng, Felix X. Yu, Cho-Jui Hsieh
2023	J	`jnl`	Federated Learning with Projected Trajectory Regularization. CoRR Tiejin Chen, Yuanpu Cao, Yujia Wang, Cho-Jui Hsieh, Jinghui Chen
2023	A*	`conf`	Improving Adversarial Robustness to Sensitivity and Invariance Attacks with Deep Metric Learning (Student Abstract). AAAI Anaelia Ovalle, Evan Czyzycki, Cho-Jui Hsieh
2023	J	`jnl`	Improving the Generation Quality of Watermarked Large Language Models via Word Importance Scoring. CoRR Yuhang Li, Yihan Wang, Zhouxing Shi, Cho-Jui Hsieh
2023	J	`jnl`	Incorporating physics into data-driven computer vision. Nat. Mac. Intell. Achuta Kadambi, Celso De Melo, Cho-Jui Hsieh, Mani B. Srivastava, Stefano Soatto
2023	J	`jnl`	MinPrompt: Graph-based Minimal Prompt Data Augmentation for Few-shot Question Answering. CoRR Xiusi Chen, Jyun-Yu Jiang, Wei-Cheng Chang, Cho-Jui Hsieh, Hsiang-Fu Yu, Wei Wang
2023	—	`conf`	NeSSA: Near-Storage Data Selection for Accelerated Machine Learning Training. HotStorage Neha Prakriya, Yu Yang, Baharan Mirzasoleiman, Cho-Jui Hsieh, Jason Cong
2023	J	`jnl`	Online Continuous Hyperparameter Optimization for Contextual Bandits. CoRR Yue Kang, Cho-Jui Hsieh, Thomas C. M. Lee
2023	J	`jnl`	PEFA: Parameter-Free Adapters for Large-scale Embedding-based Retrieval Models. CoRR Wei-Cheng Chang, Jyun-Yu Jiang, Jiong Zhang, Mutasem Al-Darabsah, Choon Hui Teo, Cho-Jui Hsieh, Hsiang-Fu Yu, S. V. N. Vishwanathan
2023	A*	`conf`	PINA: Leveraging Side Information in eXtreme Multi-label Classification via Predicted Instance Neighborhood Aggregation. ICML Eli Chien, Jiong Zhang, Cho-Jui Hsieh, Jyun-Yu Jiang, Wei-Cheng Chang, Olgica Milenkovic, Hsiang-Fu Yu
2023	J	`jnl`	PINA: Leveraging Side Information in eXtreme Multi-label Classification via Predicted Instance Neighborhood Aggregation. CoRR Eli Chien, Jiong Zhang, Cho-Jui Hsieh, Jyun-Yu Jiang, Wei-Cheng Chang, Olgica Milenkovic, Hsiang-Fu Yu
2023	J	`jnl`	Randomized Benchmarking of Local Zeroth-Order Optimizers for Variational Quantum Systems. CoRR Lucas Tecot, Cho-Jui Hsieh
2023	J	`jnl`	Red Teaming Language Model Detectors with Language Models. CoRR Zhouxing Shi, Yihan Wang, Fan Yin, Xiangning Chen, Kai-Wei Chang, Cho-Jui Hsieh
2023	A*	`conf`	Representer Point Selection for Explaining Regularized High-dimensional Models. ICML Che-Ping Tsai, Jiong Zhang, Hsiang-Fu Yu, Eli Chien, Cho-Jui Hsieh, Pradeep Kumar Ravikumar
2023	J	`jnl`	Representer Point Selection for Explaining Regularized High-dimensional Models. CoRR Che-Ping Tsai, Jiong Zhang, Eli Chien, Hsiang-Fu Yu, Cho-Jui Hsieh, Pradeep Ravikumar
2023	A*	`conf`	Robust Lipschitz Bandits to Adversarial Corruptions. NeurIPS Yue Kang, Cho-Jui Hsieh, Thomas Chun Man Lee
2023	J	`jnl`	Robust Lipschitz Bandits to Adversarial Corruptions. CoRR Yue Kang, Cho-Jui Hsieh, Thomas C. M. Lee
2023	A*	`conf`	Scaling Up Dataset Distillation to ImageNet-1K with Constant Memory. ICML Justin Cui, Ruochen Wang, Si Si, Cho-Jui Hsieh
2023	A*	`conf`	Serving Graph Compression for Graph Neural Networks. ICLR Si Si, Felix X. Yu, Ankit Singh Rawat, Cho-Jui Hsieh, Sanjiv Kumar
2023	J	`jnl`	Spatiotemporally Discriminative Video-Language Pre-Training with Text Grounding. CoRR Yuanhao Xiong, Long Zhao, Boqing Gong, Ming-Hsuan Yang, Florian Schroff, Ting Liu, Cho-Jui Hsieh, Liangzhe Yuan
2023	J	`jnl`	Stochastic Optimization for Non-convex Problem with Inexact Hessian Matrix, Gradient, and Function. CoRR Liu Liu, Xuanqing Liu, Cho-Jui Hsieh, Dacheng Tao
2023	J	`jnl`	Stochastically Controlled Compositional Gradient for Composition Problems. IEEE Trans. Neural Networks Learn. Syst. Liu Liu, Ji Liu, Cho-Jui Hsieh, Dacheng Tao
2023	A*	`conf`	Symbolic Discovery of Optimization Algorithms. NeurIPS Xiangning Chen, Chen Liang, Da Huang, Esteban Real, Kaiyuan Wang, Hieu Pham, Xuanyi Dong, Thang Luong, Cho-Jui Hsieh, Yifeng Lu, Quoc V. Le
2023	J	`jnl`	Symbolic Discovery of Optimization Algorithms. CoRR Xiangning Chen, Chen Liang, Da Huang, Esteban Real, Kaiyuan Wang, Yao Liu, Hieu Pham, Xuanyi Dong, Thang Luong, Cho-Jui Hsieh, Yifeng Lu, Quoc V. Le
2023	A*	`conf`	Towards Robustness Certification Against Universal Perturbations. ICLR Yi Zeng, Zhouxing Shi, Ming Jin, Feiyang Kang, Lingjuan Lyu, Cho-Jui Hsieh, Ruoxi Jia
2023	A*	`conf`	Training Meta-Surrogate Model for Transferable Adversarial Attack. AAAI Yunxiao Qin, Yuanhao Xiong, Jinfeng Yi, Cho-Jui Hsieh
2023	A*	`conf`	Uncertainty Quantification for Extreme Classification. SIGIR Jyun-Yu Jiang, Wei-Cheng Chang, Jiong Zhang, Cho-Jui Hsieh, Hsiang-Fu Yu
2023	A*	`conf`	Universality and Limitations of Prompt Tuning. NeurIPS Yihan Wang, Jatin Chauhan, Wei Wang, Cho-Jui Hsieh
2023	J	`jnl`	Universality and Limitations of Prompt Tuning. CoRR Yihan Wang, Jatin Chauhan, Wei Wang, Cho-Jui Hsieh
2023	A*	`conf`	Why Does Sharpness-Aware Minimization Generalize Better Than SGD? NeurIPS Zixiang Chen, Junkai Zhang, Yiwen Kou, Xiangning Chen, Cho-Jui Hsieh, Quanquan Gu
2023	J	`jnl`	Why Does Sharpness-Aware Minimization Generalize Better Than SGD? CoRR Zixiang Chen, Junkai Zhang, Yiwen Kou, Xiangning Chen, Cho-Jui Hsieh, Quanquan Gu
2022	J	`jnl`	2.5D visual relationship detection. Comput. Vis. Image Underst. Yu-Chuan Su, Soravit Changpinyo, Xiangning Chen, Sathish Thoppay, Cho-Jui Hsieh, Lior Shapira, Radu Soricut, Hartwig Adam, Matthew Brown, Ming-Hsuan Yang, Boqing Gong
2022	A*	`conf`	A Branch and Bound Framework for Stronger Adversarial Attacks of ReLU Networks. ICML Huan Zhang, Shiqi Wang, Kaidi Xu, Yihan Wang, Suman Jana, Cho-Jui Hsieh, J. Zico Kolter
2022	A*	`conf`	ADDMU: Detection of Far-Boundary Adversarial Examples with Data and Model Uncertainty Estimation. EMNLP Fan Yin, Yao Li, Cho-Jui Hsieh, Kai-Wei Chang
2022	J	`jnl`	ADDMU: Detection of Far-Boundary Adversarial Examples with Data and Model Uncertainty Estimation. CoRR Fan Yin, Yao Li, Cho-Jui Hsieh, Kai-Wei Chang
2022	A*	`conf`	Are AlphaZero-like Agents Robust to Adversarial Perturbations? NeurIPS Li-Cheng Lan, Huan Zhang, Ti-Rong Wu, Meng-Yu Tsai, I-Chen Wu, Cho-Jui Hsieh
2022	J	`jnl`	Are AlphaZero-like Agents Robust to Adversarial Perturbations? CoRR Li-Cheng Lan, Huan Zhang, Ti-Rong Wu, Meng-Yu Tsai, I-Chen Wu, Cho-Jui Hsieh
2022	A*	`conf`	CAT: Customized Adversarial Training for Improved Robustness. IJCAI Minhao Cheng, Qi Lei, Pin-Yu Chen, Inderjit S. Dhillon, Cho-Jui Hsieh
2022	J	`jnl`	Concept Gradient: Concept-based Interpretation Without Linear Assumption. CoRR Andrew Bai, Chih-Kuan Yeh, Pradeep Ravikumar, Neil Y. C. Lin, Cho-Jui Hsieh
2022	A*	`conf`	Concurrent Adversarial Learning for Large-Batch Training. ICLR Yong Liu, Xiangning Chen, Minhao Cheng, Cho-Jui Hsieh, Yang You
2022	A*	`conf`	DC-BENCH: Dataset Condensation Benchmark. NeurIPS Justin Cui, Ruochen Wang, Si Si, Cho-Jui Hsieh
2022	J	`jnl`	DC-BENCH: Dataset Condensation Benchmark. CoRR Justin Cui, Ruochen Wang, Si Si, Cho-Jui Hsieh
2022	B	`conf`	Deep Image Destruction: Vulnerability of Deep Image-to-Image Models against Adversarial Attacks. ICPR Jun-Ho Choi, Huan Zhang, Jun-Hyuk Kim, Cho-Jui Hsieh, Jong-Seok Lee
2022	A*	`conf`	ELIAS: End-to-End Learning to Index and Search in Large Output Spaces. NeurIPS Nilesh Gupta, Patrick H. Chen, Hsiang-Fu Yu, Cho-Jui Hsieh, Inderjit S. Dhillon
2022	A*	`conf`	Efficient Frameworks for Generalized Low-Rank Matrix Bandit Problems. NeurIPS Yue Kang, Cho-Jui Hsieh, Thomas Chun Man Lee
2022	A*	`conf`	Efficient Non-Parametric Optimizer Search for Diverse Tasks. NeurIPS Ruochen Wang, Yuanhao Xiong, Minhao Cheng, Cho-Jui Hsieh
2022	J	`jnl`	Efficient Non-Parametric Optimizer Search for Diverse Tasks. CoRR Ruochen Wang, Yuanhao Xiong, Minhao Cheng, Cho-Jui Hsieh
2022	A*	`conf`	Efficiently Computing Local Lipschitz Constants of Neural Networks via Bound Propagation. NeurIPS Zhouxing Shi, Yihan Wang, Huan Zhang, J. Zico Kolter, Cho-Jui Hsieh
2022	J	`jnl`	Efficiently Computing Local Lipschitz Constants of Neural Networks via Bound Propagation. CoRR Zhouxing Shi, Yihan Wang, Huan Zhang, J. Zico Kolter, Cho-Jui Hsieh
2022	J	`jnl`	End-to-End Learning to Index and Search in Large Output Spaces. CoRR Nilesh Gupta, Patrick H. Chen, Hsiang-Fu Yu, Cho-Jui Hsieh, Inderjit S. Dhillon
2022	—	`conf`	Extreme Zero-Shot Learning for Extreme Text Classification. NAACL-HLT Yuanhao Xiong, Wei-Cheng Chang, Cho-Jui Hsieh, Hsiang-Fu Yu, Inderjit S. Dhillon
2022	J	`jnl`	FINGER: Fast Inference for Graph-based Approximate Nearest Neighbor Search. CoRR Patrick H. Chen, Wei-Cheng Chang, Hsiang-Fu Yu, Inderjit S. Dhillon, Cho-Jui Hsieh
2022	J	`jnl`	FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning. CoRR Yuanhao Xiong, Ruochen Wang, Minhao Cheng, Felix X. Yu, Cho-Jui Hsieh
2022	A*	`conf`	General Cutting Planes for Bound-Propagation-Based Neural Network Verification. NeurIPS Huan Zhang, Shiqi Wang, Kaidi Xu, Linyi Li, Bo Li, Suman Jana, Cho-Jui Hsieh, J. Zico Kolter
2022	J	`jnl`	General Cutting Planes for Bound-Propagation-Based Neural Network Verification. CoRR Huan Zhang, Shiqi Wang, Kaidi Xu, Linyi Li, Bo Li, Suman Jana, Cho-Jui Hsieh, J. Zico Kolter
2022	A*	`conf`	Generalizing Few-Shot NAS with Gradient Matching. ICLR Shoukang Hu, Ruochen Wang, Lanqing Hong, Zhenguo Li, Cho-Jui Hsieh, Jiashi Feng
2022	J	`jnl`	Generalizing Few-Shot NAS with Gradient Matching. CoRR Shoukang Hu, Ruochen Wang, Lanqing Hong, Zhenguo Li, Cho-Jui Hsieh, Jiashi Feng
2022	J	`jnl`	Improving Adversarial Robustness to Sensitivity and Invariance Attacks with Deep Metric Learning. CoRR Anaelia Ovalle, Evan Czyzycki, Cho-Jui Hsieh
2022	—	`conf`	Improving the Adversarial Robustness of NLP Models by Information Bottleneck. ACL (Findings) Cenyuan Zhang, Xiang Zhou, Yixin Wan, Xiaoqing Zheng, Kai-Wei Chang, Cho-Jui Hsieh
2022	J	`jnl`	Improving the Adversarial Robustness of NLP Models by Information Bottleneck. CoRR Cenyuan Zhang, Xiang Zhou, Yixin Wan, Xiaoqing Zheng, Kai-Wei Chang, Cho-Jui Hsieh
2022	—	`conf`	Learning to Learn with Smooth Regularization. ECCV (23) Yuanhao Xiong, Cho-Jui Hsieh
2022	A*	`conf`	Learning to Schedule Learning rate with Graph Neural Networks. ICLR Yuanhao Xiong, Li-Cheng Lan, Xiangning Chen, Ruochen Wang, Cho-Jui Hsieh
2022	J	`jnl`	Local Critic Training for Model-Parallel Learning of Deep Neural Networks. IEEE Trans. Neural Networks Learn. Syst. Hojung Lee, Cho-Jui Hsieh, Jong-Seok Lee
2022	A*	`conf`	Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction. ICLR Eli Chien, Wei-Cheng Chang, Cho-Jui Hsieh, Hsiang-Fu Yu, Jiong Zhang, Olgica Milenkovic, Inderjit S. Dhillon
2022	J	`jnl`	On the Adversarial Robustness of Vision Transformers. Trans. Mach. Learn. Res. Rulin Shao, Zhouxing Shi, Jinfeng Yi, Pin-Yu Chen, Cho-Jui Hsieh
2022	A*	`conf`	On the Convergence of Certified Robust Training with Interval Bound Propagation. ICLR Yihan Wang, Zhouxing Shi, Quanquan Gu, Cho-Jui Hsieh
2022	J	`jnl`	On the Convergence of Certified Robust Training with Interval Bound Propagation. CoRR Yihan Wang, Zhouxing Shi, Quanquan Gu, Cho-Jui Hsieh
2022	—	`conf`	On the Sensitivity and Stability of Model Interpretations in NLP. ACL (1) Fan Yin, Zhouxing Shi, Cho-Jui Hsieh, Kai-Wei Chang
2022	A*	`conf`	PECOS: Prediction for Enormous and Correlated Output Spaces. KDD Hsiang-Fu Yu, Jiong Zhang, Wei-Cheng Chang, Jyun-Yu Jiang, Wei Li, Cho-Jui Hsieh
2022	J	`jnl`	Preserving In-Context Learning ability in Large Language Model Fine-tuning. CoRR Yihan Wang, Si Si, Daliang Li, Michal Lukasik, Felix X. Yu, Cho-Jui Hsieh, Inderjit S. Dhillon, Sanjiv Kumar
2022	A*	`conf`	Random Sharpness-Aware Minimization. NeurIPS Yong Liu, Siqi Mai, Minhao Cheng, Xiangning Chen, Cho-Jui Hsieh, Yang You
2022	J	`jnl`	Reducing Training Sample Memorization in GANs by Training with Memorization Rejection. CoRR Andrew Bai, Cho-Jui Hsieh, Wendy Chi-wen Kan, Hsuan-Tien Lin
2022	A*	`conf`	Relevance under the Iceberg: Reasonable Prediction for Extreme Multi-label Classification. SIGIR Jyun-Yu Jiang, Wei-Cheng Chang, Jiong Zhang, Cho-Jui Hsieh, Hsiang-Fu Yu
2022	A	`conf`	Robust Stochastic Linear Contextual Bandits Under Adversarial Attacks. AISTATS Qin Ding, Cho-Jui Hsieh, James Sharpnack
2022	B	`conf`	Robust Text CAPTCHAs Using Adversarial Examples. IEEE Big Data Rulin Shao, Zhouxing Shi, Jinfeng Yi, Pin-Yu Chen, Cho-Jui Hsieh
2022	J	`jnl`	Scaling Up Dataset Distillation to ImageNet-1K with Constant Memory. CoRR Justin Cui, Ruochen Wang, Si Si, Cho-Jui Hsieh
2022	A*	`conf`	Syndicated Bandits: A Framework for Auto Tuning Hyper-parameters in Contextual Bandit Algorithms. NeurIPS Qin Ding, Yue Kang, Yi-Wei Liu, Thomas Chun Man Lee, Cho-Jui Hsieh, James Sharpnack
2022	A*	`conf`	The Fourth Workshop on Adversarial Learning Methods for Machine Learning and Data Mining (AdvML 2022). KDD Pin-Yu Chen, Cho-Jui Hsieh, Bo Li, Sijia Liu
2022	—	`conf`	Towards Adversarially Robust Text Classifiers by Learning to Reweight Clean Examples. ACL (Findings) Jianhan Xu, Cenyuan Zhang, Xiaoqing Zheng, Linyang Li, Cho-Jui Hsieh, Kai-Wei Chang, Xuanjing Huang
2022	A*	`conf`	Towards Efficient and Scalable Sharpness-Aware Minimization. CVPR Yong Liu, Siqi Mai, Xiangning Chen, Cho-Jui Hsieh, Yang You
2022	J	`jnl`	Towards Efficient and Scalable Sharpness-Aware Minimization. CoRR Yong Liu, Siqi Mai, Xiangning Chen, Cho-Jui Hsieh, Yang You
2022	J	`jnl`	Uncertainty in Extreme Multi-label Classification. CoRR Jyun-Yu Jiang, Wei-Cheng Chang, Jiong Zhang, Cho-Jui Hsieh, Hsiang-Fu Yu
2022	J	`jnl`	Watermarking Pre-trained Language Models with Backdooring. CoRR Chenxi Gu, Chengsong Huang, Xiaoqing Zheng, Kai-Wei Chang, Cho-Jui Hsieh
2022	—	`conf`	Weight Perturbation as Defense against Adversarial Word Substitutions. EMNLP (Findings) Jianhan Xu, Linyang Li, Jiping Zhang, Xiaoqing Zheng, Kai-Wei Chang, Cho-Jui Hsieh, Xuanjing Huang
2022	A*	`conf`	When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations. ICLR Xiangning Chen, Cho-Jui Hsieh, Boqing Gong
2021	J	`jnl`	2.5D Visual Relationship Detection. CoRR Yu-Chuan Su, Soravit Changpinyo, Xiangning Chen, Sathish Thoppay, Cho-Jui Hsieh, Lior Shapira, Radu Soricut, Hartwig Adam, Matthew Brown, Ming-Hsuan Yang, Boqing Gong
2021	J	`jnl`	A Review of Adversarial Attack and Defense for Classification Methods. CoRR Yao Li, Minhao Cheng, Cho-Jui Hsieh, Thomas C. M. Lee
2021	J	`jnl`	Adversarial Attack across Datasets. CoRR Yunxiao Qin, Yuanhao Xiong, Jinfeng Yi, Cho-Jui Hsieh
2021	A	`conf`	An Efficient Algorithm For Generalized Linear Bandit: Online Stochastic Gradient Descent and Thompson Sampling. AISTATS Qin Ding, Cho-Jui Hsieh, James Sharpnack
2021	J	`jnl`	Balancing Robustness and Sensitivity using Feature Contrastive Learning. CoRR Seungyeon Kim, Daniel Glasner, Srikumar Ramalingam, Cho-Jui Hsieh, Kishore Papineni, Sanjiv Kumar
2021	J	`jnl`	Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Complete and Incomplete Neural Network Verification. CoRR Shiqi Wang, Huan Zhang, Kaidi Xu, Xue Lin, Suman Jana, Cho-Jui Hsieh, J. Zico Kolter
2021	A*	`conf`	Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Neural Network Robustness Verification. NeurIPS Shiqi Wang, Huan Zhang, Kaidi Xu, Xue Lin, Suman Jana, Cho-Jui Hsieh, J. Zico Kolter
2021	J	`jnl`	Can Vision Transformers Perform Convolution? CoRR Shanda Li, Xiangning Chen, Di He, Cho-Jui Hsieh
2021	J	`jnl`	Communication-avoiding kernel ridge regression on parallel and distributed systems. CCF Trans. High Perform. Comput. Yang You, Jingyue Huang, Cho-Jui Hsieh, Richard W. Vuduc, James Demmel
2021	J	`jnl`	Concurrent Adversarial Learning for Large-Batch Training. CoRR Yong Liu, Xiangning Chen, Minhao Cheng, Cho-Jui Hsieh, Yang You
2021	A*	`conf`	DRONE: Data-aware Low-rank Compression for Large NLP Models. NeurIPS Patrick H. Chen, Hsiang-Fu Yu, Inderjit S. Dhillon, Cho-Jui Hsieh
2021	J	`jnl`	Deep Image Destruction: A Comprehensive Study on Vulnerability of Deep Image-to-Image Models against Adversarial Attacks. CoRR Jun-Ho Choi, Huan Zhang, Jun-Hyuk Kim, Cho-Jui Hsieh, Jong-Seok Lee
2021	—	`conf`	Defense against Synonym Substitution-based Adversarial Attacks via Dirichlet Neighborhood Ensemble. ACL/IJCNLP (1) Yi Zhou, Xiaoqing Zheng, Cho-Jui Hsieh, Kai-Wei Chang, Xuanjing Huang
2021	J	`jnl`	Detecting Adversarial Examples with Bayesian Neural Network. CoRR Yao Li, Tongyi Tang, Cho-Jui Hsieh, Thomas C. M. Lee
2021	—	`conf`	Double Perturbation: On the Robustness of Robustness and Counterfactual Bias Evaluation. NAACL-HLT Chong Zhang, Jieyu Zhao, Huan Zhang, Kai-Wei Chang, Cho-Jui Hsieh
2021	J	`jnl`	Double Perturbation: On the Robustness of Robustness and Counterfactual Bias Evaluation. CoRR Chong Zhang, Jieyu Zhao, Huan Zhang, Kai-Wei Chang, Cho-Jui Hsieh
2021	A*	`conf`	DrNAS: Dirichlet Neural Architecture Search. ICLR Xiangning Chen, Ruochen Wang, Minhao Cheng, Xiaocheng Tang, Cho-Jui Hsieh
2021	A*	`conf`	DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification. NeurIPS Yongming Rao, Wenliang Zhao, Benlin Liu, Jiwen Lu, Jie Zhou, Cho-Jui Hsieh
2021	J	`jnl`	DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification. CoRR Yongming Rao, Wenliang Zhao, Benlin Liu, Jiwen Lu, Jie Zhou, Cho-Jui Hsieh
2021	J	`jnl`	Emotional EEG Classification using Connectivity Features and Convolutional Neural Networks. CoRR Seong-Eun Moon, Chun-Jui Chen, Cho-Jui Hsieh, Jane-Ling Wang, Jong-Seok Lee
2021	A*	`conf`	Evaluations and Methods for Explanation through Robustness Analysis. ICLR Cheng-Yu Hsieh, Chih-Kuan Yeh, Xuanqing Liu, Pradeep Kumar Ravikumar, Seungyeon Kim, Sanjiv Kumar, Cho-Jui Hsieh
2021	J	`jnl`	Extreme Zero-Shot Learning for Extreme Text Classification. CoRR Yuanhao Xiong, Wei-Cheng Chang, Cho-Jui Hsieh, Hsiang-Fu Yu, Inderjit S. Dhillon
2021	J	`jnl`	Fast Certified Robust Training via Better Initialization and Shorter Warmup. CoRR Zhouxing Shi, Yihan Wang, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh
2021	A*	`conf`	Fast Certified Robust Training with Short Warmup. NeurIPS Zhouxing Shi, Yihan Wang, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh
2021	A*	`conf`	Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers. ICLR Kaidi Xu, Huan Zhang, Shiqi Wang, Yihan Wang, Suman Jana, Xue Lin, Cho-Jui Hsieh
2021	J	`jnl`	How and When Adversarial Robustness Transfers in Knowledge Distillation? CoRR Rulin Shao, Jinfeng Yi, Pin-Yu Chen, Cho-Jui Hsieh
2021	A*	`conf`	Label Disentanglement in Partition-based Extreme Multilabel Classification. NeurIPS Xuanqing Liu, Wei-Cheng Chang, Hsiang-Fu Yu, Cho-Jui Hsieh, Inderjit S. Dhillon
2021	J	`jnl`	Label Disentanglement in Partition-based Extreme Multilabel Classification. CoRR Xuanqing Liu, Wei-Cheng Chang, Hsiang-Fu Yu, Cho-Jui Hsieh, Inderjit S. Dhillon
2021	J	`jnl`	Learnable Fourier Features for Multi-Dimensional Spatial Positional Encoding. CoRR Yang Li, Si Si, Gang Li, Cho-Jui Hsieh, Samy Bengio
2021	A*	`conf`	Learnable Fourier Features for Multi-dimensional Spatial Positional Encoding. NeurIPS Yang Li, Si Si, Gang Li, Cho-Jui Hsieh, Samy Bengio
2021	A*	`conf`	Learning to Stop: Dynamic Simulation Monte-Carlo Tree Search. AAAI Li-Cheng Lan, Ti-Rong Wu, I-Chen Wu, Cho-Jui Hsieh
2021	J	`jnl`	Local Critic Training for Model-Parallel Learning of Deep Neural Networks. CoRR Hojung Lee, Cho-Jui Hsieh, Jong-Seok Lee
2021	A*	`conf`	Measures and Best Practices for Responsible AI. KDD Sunipa Dev, Mehrnoosh Sameki, Jwala Dhamala, Cho-Jui Hsieh
2021	A*	`conf`	Multi-Proxy Wasserstein Classifier for Image Classification. AAAI Benlin Liu, Yongming Rao, Jiwen Lu, Jie Zhou, Cho-Jui Hsieh
2021	J	`jnl`	Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction. CoRR Eli Chien, Wei-Cheng Chang, Cho-Jui Hsieh, Hsiang-Fu Yu, Jiong Zhang, Olgica Milenkovic, Inderjit S. Dhillon
2021	J	`jnl`	On the Adversarial Robustness of Visual Transformers. CoRR Rulin Shao, Zhouxing Shi, Jinfeng Yi, Pin-Yu Chen, Cho-Jui Hsieh
2021	J	`jnl`	On the Faithfulness Measurements for Model Interpretations. CoRR Fan Yin, Zhouxing Shi, Cho-Jui Hsieh, Kai-Wei Chang
2021	—	`conf`	On the Transferability of Adversarial Attacks against Neural Text Classifier. EMNLP (1) Liping Yuan, Xiaoqing Zheng, Yi Zhou, Cho-Jui Hsieh, Kai-Wei Chang
2021	A*	`conf`	Overcoming Catastrophic Forgetting by Bayesian Generative Regularization. ICML Pei-Hung Chen, Wei Wei, Cho-Jui Hsieh, Bo Dai
2021	A*	`conf`	RANK-NOSH: Efficient Predictor-Based Architecture Search via Non-Uniform Successive Halving. ICCV Ruochen Wang, Xiangning Chen, Minhao Cheng, Xiaocheng Tang, Cho-Jui Hsieh
2021	J	`jnl`	RANK-NOSH: Efficient Predictor-Based Architecture Search via Non-Uniform Successive Halving. CoRR Ruochen Wang, Xiangning Chen, Minhao Cheng, Xiaocheng Tang, Cho-Jui Hsieh
2021	A*	`conf`	RandomRooms: Unsupervised Pre-training from Synthetic Shapes and Randomized Layouts for 3D Object Detection. ICCV Yongming Rao, Benlin Liu, Yi Wei, Jiwen Lu, Cho-Jui Hsieh, Jie Zhou
2021	J	`jnl`	RandomRooms: Unsupervised Pre-training from Synthetic Shapes and Randomized Layouts for 3D Object Detection. CoRR Yongming Rao, Benlin Liu, Yi Wei, Jiwen Lu, Cho-Jui Hsieh, Jie Zhou
2021	A*	`conf`	Rethinking Architecture Selection in Differentiable NAS. ICLR Ruochen Wang, Minhao Cheng, Xiangning Chen, Xiaocheng Tang, Cho-Jui Hsieh
2021	J	`jnl`	Rethinking Architecture Selection in Differentiable NAS. CoRR Ruochen Wang, Minhao Cheng, Xiangning Chen, Xiaocheng Tang, Cho-Jui Hsieh
2021	A*	`conf`	Robust Reinforcement Learning on State Observations with Learned Optimal Adversary. ICLR Huan Zhang, Hongge Chen, Duane S. Boning, Cho-Jui Hsieh
2021	J	`jnl`	Robust Reinforcement Learning on State Observations with Learned Optimal Adversary. CoRR Huan Zhang, Hongge Chen, Duane S. Boning, Cho-Jui Hsieh
2021	J	`jnl`	Robust Stochastic Linear Contextual Bandits Under Adversarial Attacks. CoRR Qin Ding, Cho-Jui Hsieh, James Sharpnack
2021	J	`jnl`	Robust Text CAPTCHAs Using Adversarial Examples. CoRR Rulin Shao, Zhouxing Shi, Jinfeng Yi, Pin-Yu Chen, Cho-Jui Hsieh
2021	A*	`conf`	Robust and Accurate Object Detection via Adversarial Learning. CVPR Xiangning Chen, Cihang Xie, Mingxing Tan, Li Zhang, Cho-Jui Hsieh, Boqing Gong
2021	J	`jnl`	Robust and Accurate Object Detection via Adversarial Learning. CoRR Xiangning Chen, Cihang Xie, Mingxing Tan, Li Zhang, Cho-Jui Hsieh, Boqing Gong
2021	—	`conf`	Searching for an Effective Defender: Benchmarking Defense against Adversarial Word Substitution. EMNLP (1) Zongyi Li, Jianhan Xu, Jiehang Zeng, Linyang Li, Xiaoqing Zheng, Qi Zhang, Kai-Wei Chang, Cho-Jui Hsieh
2021	J	`jnl`	Searching for an Effective Defender: Benchmarking Defense against Adversarial Word Substitution. CoRR Zongyi Li, Jianhan Xu, Jiehang Zeng, Linyang Li, Xiaoqing Zheng, Qi Zhang, Kai-Wei Chang, Cho-Jui Hsieh
2021	A*	`conf`	Self-Progressing Robust Training. AAAI Minhao Cheng, Pin-Yu Chen, Sijia Liu, Shiyu Chang, Cho-Jui Hsieh, Payel Das
2021	J	`jnl`	Syndicated Bandits: A Framework for Auto Tuning Hyper-parameters in Contextual Bandit Algorithms. CoRR Qin Ding, Yi-Wei Liu, Cho-Jui Hsieh, James Sharpnack
2021	J	`jnl`	Temporal Shuffling for Defending Deep Action Recognition Models against Adversarial Attacks. CoRR Jaehui Hwang, Huan Zhang, Jun-Ho Choi, Cho-Jui Hsieh, Jong-Seok Lee
2021	A*	`conf`	Third Workshop on Adversarial Learning Methods for Machine Learning and Data Mining (AdvML 2021). KDD Pin-Yu Chen, Cho-Jui Hsieh, Bo Li, Sijia Liu
2021	A*	`conf`	Towards Robustness of Deep Neural Networks via Regularization. ICCV Yao Li, Martin Renqiang Min, Thomas C. M. Lee, Wenchao Yu, Erik Kruus, Wei Wang, Cho-Jui Hsieh
2021	J	`jnl`	Training Meta-Surrogate Model for Transferable Adversarial Attack. CoRR Yunxiao Qin, Yuanhao Xiong, Jinfeng Yi, Cho-Jui Hsieh
2021	J	`jnl`	When Vision Transformers Outperform ResNets without Pretraining or Strong Data Augmentations. CoRR Xiangning Chen, Cho-Jui Hsieh, Boqing Gong
2020	—	`conf`	Adversarially Robust Deep Image Super-Resolution Using Entropy Regularization. ACCV (4) Jun-Ho Choi, Huan Zhang, Jun-Hyuk Kim, Cho-Jui Hsieh, Jong-Seok Lee
2020	A*	`conf`	An Efficient Adversarial Attack for Tree Ensembles. NeurIPS Chong Zhang, Huan Zhang, Cho-Jui Hsieh
2020	J	`jnl`	An Efficient Adversarial Attack for Tree Ensembles. CoRR Chong Zhang, Huan Zhang, Cho-Jui Hsieh
2020	J	`jnl`	An Efficient Algorithm For Generalized Linear Bandit: Online Stochastic Gradient Descent and Thompson Sampling. CoRR Qin Ding, Cho-Jui Hsieh, James Sharpnack
2020	A*	`conf`	Automatic Perturbation Analysis for Scalable Certified Robustness and Beyond. NeurIPS Kaidi Xu, Zhouxing Shi, Huan Zhang, Yihan Wang, Kai-Wei Chang, Minlie Huang, Bhavya Kailkhura, Xue Lin, Cho-Jui Hsieh
2020	J	`jnl`	Automatic Perturbation Analysis on General Computational Graphs. CoRR Kaidi Xu, Zhouxing Shi, Huan Zhang, Minlie Huang, Kai-Wei Chang, Bhavya Kailkhura, Xue Lin, Cho-Jui Hsieh
2020	J	`jnl`	CAT: Customized Adversarial Training for Improved Robustness. CoRR Minhao Cheng, Qi Lei, Pin-Yu Chen, Inderjit S. Dhillon, Cho-Jui Hsieh
2020	A*	`conf`	Clustering and Constructing User Coresets to Accelerate Large-scale Top-K Recommender Systems. WWW Jyun-Yu Jiang, Patrick H. Chen, Cho-Jui Hsieh, Wei Wang
2020	J	`jnl`	Defense against Adversarial Attacks in NLP via Dirichlet Neighborhood Ensemble. CoRR Yi Zhou, Xiaoqing Zheng, Cho-Jui Hsieh, Kai-Wei Chang, Xuanjing Huang
2020	J	`jnl`	DrNAS: Dirichlet Neural Architecture Search. CoRR Xiangning Chen, Ruochen Wang, Minhao Cheng, Xiaocheng Tang, Cho-Jui Hsieh
2020	A*	`conf`	Efficient Neural Interaction Function Search for Collaborative Filtering. WWW Quanming Yao, Xiangning Chen, James T. Kwok, Yong Li, Cho-Jui Hsieh
2020	A*	`conf`	Elastic-InfoGAN: Unsupervised Disentangled Representation Learning in Class-Imbalanced Data. NeurIPS Utkarsh Ojha, Krishna Kumar Singh, Cho-Jui Hsieh, Yong Jae Lee
2020	J	`jnl`	Emotional EEG classification using connectivity features and convolutional neural networks. Neural Networks Seong-Eun Moon, Chun-Jui Chen, Cho-Jui Hsieh, Jane-Ling Wang, Jong-Seok Lee
2020	A*	`conf`	Evaluating and Enhancing the Robustness of Neural Network-based Dependency Parsing Models with Adversarial Examples. ACL Xiaoqing Zheng, Jiehang Zeng, Yi Zhou, Cho-Jui Hsieh, Minhao Cheng, Xuanjing Huang
2020	J	`jnl`	Evaluations and Methods for Explanation through Robustness Analysis. CoRR Cheng-Yu Hsieh, Chih-Kuan Yeh, Xuanqing Liu, Pradeep Ravikumar, Seungyeon Kim, Sanjiv Kumar, Cho-Jui Hsieh
2020	J	`jnl`	Fast LSTM by dynamic decomposition on cloud and distributed systems. Knowl. Inf. Syst. Yang You, Yuxiong He, Samyam Rajbhandari, Wenhan Wang, Cho-Jui Hsieh, Kurt Keutzer, James Demmel
2020	J	`jnl`	Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers. CoRR Kaidi Xu, Huan Zhang, Shiqi Wang, Yihan Wang, Suman Jana, Xue Lin, Cho-Jui Hsieh
2020	J	`jnl`	Generating universal language adversarial examples by understanding and enhancing the transferability across neural models. CoRR Liping Yuan, Xiaoqing Zheng, Yi Zhou, Cho-Jui Hsieh, Kai-Wei Chang, Xuanjing Huang
2020	A	`conf`	Graph DNA: Deep Neighborhood Aware Graph Encoding for Collaborative Filtering. AISTATS Liwei Wu, Hsiang-Fu Yu, Nikhil Rao, James Sharpnack, Cho-Jui Hsieh
2020	J	`jnl`	Greedy Attack and Gumbel Attack: Generating Adversarial Examples for Discrete Data. J. Mach. Learn. Res. Puyudi Yang, Jianbo Chen, Cho-Jui Hsieh, Jane-Ling Wang, Michael I. Jordan
2020	A*	`conf`	How Does Noise Help Robustness? Explanation and Exploration under the Neural SDE Framework. CVPR Xuanqing Liu, Tesi Xiao, Si Si, Qin Cao, Sanjiv Kumar, Cho-Jui Hsieh
2020	J	`jnl`	How much progress have we made in neural network training? A New Evaluation Protocol for Benchmarking Optimizers. CoRR Yuanhao Xiong, Xuanqing Liu, Li-Cheng Lan, Yang You, Si Si, Cho-Jui Hsieh
2020	—	`conf`	Improved Adversarial Training via Learned Optimizer. ECCV (8) Yuanhao Xiong, Cho-Jui Hsieh
2020	J	`jnl`	Improved Adversarial Training via Learned Optimizer. CoRR Yuanhao Xiong, Cho-Jui Hsieh
2020	J	`jnl`	Improving the Speed and Quality of GAN by Adversarial Training. CoRR Jiachen Zhong, Xuanqing Liu, Cho-Jui Hsieh
2020	A*	`conf`	Large Batch Optimization for Deep Learning: Training BERT in 76 minutes. ICLR Yang You, Jing Li, Sashank J. Reddi, Jonathan Hseu, Sanjiv Kumar, Srinadh Bhojanapalli, Xiaodan Song, James Demmel, Kurt Keutzer, Cho-Jui Hsieh
2020	A*	`conf`	Learning to Encode Position for Transformer with Continuous Dynamical Model. ICML Xuanqing Liu, Hsiang-Fu Yu, Inderjit S. Dhillon, Cho-Jui Hsieh
2020	J	`jnl`	Learning to Encode Position for Transformer with Continuous Dynamical Model. CoRR Xuanqing Liu, Hsiang-Fu Yu, Inderjit S. Dhillon, Cho-Jui Hsieh
2020	A*	`conf`	Learning to Learn by Zeroth-Order Oracle. ICLR Yangjun Ruan, Yuanhao Xiong, Sashank J. Reddi, Sanjiv Kumar, Cho-Jui Hsieh
2020	J	`jnl`	Learning to Stop: Dynamic Simulation Monte-Carlo Tree Search. CoRR Li-Cheng Lan, Meng-Yu Tsai, Ti-Rong Wu, I-Chen Wu, Cho-Jui Hsieh
2020	A*	`conf`	MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius. ICLR Runtian Zhai, Chen Dan, Di He, Huan Zhang, Boqing Gong, Pradeep Ravikumar, Cho-Jui Hsieh, Liwei Wang
2020	J	`jnl`	MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius. CoRR Runtian Zhai, Chen Dan, Di He, Huan Zhang, Boqing Gong, Pradeep Ravikumar, Cho-Jui Hsieh, Liwei Wang
2020	A*	`conf`	ML-LOO: Detecting Adversarial Examples with Feature Attribution. AAAI Puyudi Yang, Jianbo Chen, Cho-Jui Hsieh, Jane-Ling Wang, Michael I. Jordan
2020	—	`conf`	MetaDistiller: Network Self-Boosting via Meta-Learned Top-Down Distillation. ECCV (14) Benlin Liu, Yongming Rao, Jiwen Lu, Jie Zhou, Cho-Jui Hsieh
2020	J	`jnl`	MetaDistiller: Network Self-Boosting via Meta-Learned Top-Down Distillation. CoRR Benlin Liu, Yongming Rao, Jiwen Lu, Jie Zhou, Cho-Jui Hsieh
2020	A*	`conf`	Multi-Stage Influence Function. NeurIPS Hongge Chen, Si Si, Yang Li, Ciprian Chelba, Sanjiv Kumar, Duane S. Boning, Cho-Jui Hsieh
2020	J	`jnl`	Multi-Stage Influence Function. CoRR Hongge Chen, Si Si, Yang Li, Ciprian Chelba, Sanjiv Kumar, Duane S. Boning, Cho-Jui Hsieh
2020	J	`jnl`	Multiscale Non-stationary Stochastic Bandits. CoRR Qin Ding, Cho-Jui Hsieh, James Sharpnack
2020	A*	`conf`	On Lp-norm Robustness of Ensemble Decision Stumps and Trees. ICML Yihan Wang, Huan Zhang, Hongge Chen, Duane S. Boning, Cho-Jui Hsieh
2020	J	`jnl`	On 𝓁 CoRR Yihan Wang, Huan Zhang, Hongge Chen, Duane S. Boning, Cho-Jui Hsieh
2020	A*	`conf`	Provably Robust Metric Learning. NeurIPS Lu Wang, Xuanqing Liu, Jinfeng Yi, Yuan Jiang, Cho-Jui Hsieh
2020	J	`jnl`	Provably Robust Metric Learning. CoRR Lu Wang, Xuanqing Liu, Jinfeng Yi, Yuan Jiang, Cho-Jui Hsieh
2020	J	`jnl`	Robust Deep Reinforcement Learning against Adversarial Perturbations on Observations. CoRR Huan Zhang, Hongge Chen, Chaowei Xiao, Bo Li, Duane S. Boning, Cho-Jui Hsieh
2020	A*	`conf`	Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations. NeurIPS Huan Zhang, Hongge Chen, Chaowei Xiao, Bo Li, Mingyan Liu, Duane S. Boning, Cho-Jui Hsieh
2020	A*	`conf`	Robustness Verification for Transformers. ICLR Zhouxing Shi, Huan Zhang, Kai-Wei Chang, Minlie Huang, Cho-Jui Hsieh
2020	J	`jnl`	Robustness Verification for Transformers. CoRR Zhouxing Shi, Huan Zhang, Kai-Wei Chang, Minlie Huang, Cho-Jui Hsieh
2020	A	`conf`	SSE-PT: Sequential Recommendation Via Personalized Transformer. RecSys Liwei Wu, Shuqing Li, Cho-Jui Hsieh, James Sharpnack
2020	J	`jnl`	Self-Progressing Robust Training. CoRR Minhao Cheng, Pin-Yu Chen, Sijia Liu, Shiyu Chang, Cho-Jui Hsieh, Payel Das
2020	A*	`conf`	Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples. AAAI Minhao Cheng, Jinfeng Yi, Pin-Yu Chen, Huan Zhang, Cho-Jui Hsieh
2020	A*	`conf`	Sign-OPT: A Query-Efficient Hard-label Adversarial Attack. ICLR Minhao Cheng, Simranjit Singh, Patrick H. Chen, Pin-Yu Chen, Sijia Liu, Cho-Jui Hsieh
2020	J	`jnl`	Spanning Attack: Reinforce Black-box Attacks with Unlabeled Data. CoRR Lu Wang, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, Yuan Jiang
2020	J	`jnl`	Spanning attack: reinforce black-box attacks with unlabeled data. Mach. Learn. Lu Wang, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, Yuan Jiang
2020	A*	`conf`	Stabilizing Differentiable Architecture Search via Perturbation-based Regularization. ICML Xiangning Chen, Cho-Jui Hsieh
2020	J	`jnl`	Stabilizing Differentiable Architecture Search via Perturbation-based Regularization. CoRR Xiangning Chen, Cho-Jui Hsieh
2020	J	`jnl`	The Limit of the Batch Size. CoRR Yang You, Yuhui Wang, Huan Zhang, Zhao Zhang, James Demmel, Cho-Jui Hsieh
2020	A*	`conf`	Towards Stable and Efficient Training of Verifiably Robust Neural Networks. ICLR Huan Zhang, Hongge Chen, Chaowei Xiao, Sven Gowal, Robert Stanforth, Bo Li, Duane S. Boning, Cho-Jui Hsieh
2020	J	`jnl`	Voting based ensemble improves robustness of defensive models. CoRR Devvrit, Minhao Cheng, Cho-Jui Hsieh, Inderjit S. Dhillon
2020	A*	`conf`	What Does BERT with Vision Look At? ACL Liunian Harold Li, Mark Yatskar, Da Yin, Cho-Jui Hsieh, Kai-Wei Chang
2019	A*	`conf`	A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks. NeurIPS Hadi Salman, Greg Yang, Huan Zhang, Cho-Jui Hsieh, Pengchuan Zhang
2019	J	`jnl`	A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks. CoRR Hadi Salman, Greg Yang, Huan Zhang, Cho-Jui Hsieh, Pengchuan Zhang
2019	A	`conf`	A Fast Sampling Algorithm for Maximum Inner Product Search. AISTATS Qin Ding, Hsiang-Fu Yu, Cho-Jui Hsieh
2019	A*	`conf`	A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning. NeurIPS Xuanqing Liu, Si Si, Jerry Zhu, Yang Li, Cho-Jui Hsieh
2019	J	`jnl`	A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning. CoRR Xuanqing Liu, Si Si, Xiaojin Zhu, Yang Li, Cho-Jui Hsieh
2019	—	`conf`	Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network. ICLR (Poster) Xuanqing Liu, Yao Li, Chongruo Wu, Cho-Jui Hsieh
2019	A*	`conf`	AutoZOOM: Autoencoder-Based Zeroth Order Optimization Method for Attacking Black-Box Neural Networks. AAAI Chun-Chen Tu, Pai-Shun Ting, Pin-Yu Chen, Sijia Liu, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, Shin-Ming Cheng
2019	A*	`conf`	Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks. KDD Wei-Lin Chiang, Xuanqing Liu, Si Si, Yang Li, Samy Bengio, Cho-Jui Hsieh
2019	J	`jnl`	Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks. CoRR Wei-Lin Chiang, Xuanqing Liu, Si Si, Yang Li, Samy Bengio, Cho-Jui Hsieh
2019	J	`jnl`	Convergence of Adversarial Training in Overparametrized Networks. CoRR Ruiqi Gao, Tianle Cai, Haochuan Li, Liwei Wang, Cho-Jui Hsieh, Jason D. Lee
2019	A*	`conf`	Convergence of Adversarial Training in Overparametrized Neural Networks. NeurIPS Ruiqi Gao, Tianle Cai, Haochuan Li, Cho-Jui Hsieh, Liwei Wang, Jason D. Lee
2019	J	`jnl`	Efficient Contextual Representation Learning With Continuous Outputs. Trans. Assoc. Comput. Linguistics Liunian Harold Li, Patrick H. Chen, Cho-Jui Hsieh, Kai-Wei Chang
2019	J	`jnl`	Efficient Contextual Representation Learning Without Softmax Layer. CoRR Liunian Harold Li, Patrick H. Chen, Cho-Jui Hsieh, Kai-Wei Chang
2019	J	`jnl`	Elastic-InfoGAN: Unsupervised Disentangled Representation Learning in Imbalanced Data. CoRR Utkarsh Ojha, Krishna Kumar Singh, Cho-Jui Hsieh, Yong Jae Lee
2019	J	`jnl`	Enhancing Certifiable Robustness via a Deep Model Ensemble. CoRR Huan Zhang, Minhao Cheng, Cho-Jui Hsieh
2019	A*	`conf`	Evaluating Robustness of Deep Image Super-Resolution Against Adversarial Attacks. ICCV Jun-Ho Choi, Huan Zhang, Jun-Hyuk Kim, Cho-Jui Hsieh, Jong-Seok Lee
2019	J	`jnl`	Evaluating Robustness of Deep Image Super-Resolution against Adversarial Attacks. CoRR Jun-Ho Choi, Huan Zhang, Jun-Hyuk Kim, Cho-Jui Hsieh, Jong-Seok Lee
2019	—	`conf`	Evaluating and Enhancing the Robustness of Dialogue Systems: A Case Study on a Negotiation Agent. NAACL-HLT (1) Minhao Cheng, Wei Wei, Cho-Jui Hsieh
2019	J	`jnl`	Evaluating the Robustness of Nearest Neighbor Classifiers: A Primal-Dual Perspective. CoRR Lu Wang, Xuanqing Liu, Jinfeng Yi, Zhi-Hua Zhou, Cho-Jui Hsieh
2019	J	`jnl`	Fast Deep Neural Network Training on Distributed Systems and Cloud TPUs. IEEE Trans. Parallel Distributed Syst. Yang You, Zhao Zhang, Cho-Jui Hsieh, James Demmel, Kurt Keutzer
2019	A*	`conf`	Fast LSTM Inference by Dynamic Decomposition on Cloud Systems. ICDM Yang You, Yuxiong He, Samyam Rajbhandari, Wenhan Wang, Cho-Jui Hsieh, Kurt Keutzer, James Demmel
2019	A	`conf`	Fast Training for Large-Scale One-versus-All Linear Classifiers using Tree-Structured Initialization. SDM Huang Fang, Minhao Cheng, Cho-Jui Hsieh, Michael P. Friedlander
2019	A	`conf`	GenAttack: practical black-box attacks with gradient-free optimization. GECCO Moustafa Alzantot, Yash Sharma, Supriyo Chakraborty, Huan Zhang, Cho-Jui Hsieh, Mani B. Srivastava
2019	J	`jnl`	Graph DNA: Deep Neighborhood Aware Graph Encoding for Collaborative Filtering. CoRR Liwei Wu, Hsiang-Fu Yu, Nikhil Rao, James Sharpnack, Cho-Jui Hsieh
2019	J	`jnl`	GraphDefense: Towards Robust Graph Convolutional Networks. CoRR Xiaoyun Wang, Xuanqing Liu, Cho-Jui Hsieh
2019	J	`jnl`	Large-Batch Training for LSTM and Beyond. CoRR Yang You, Jonathan Hseu, Chris Ying, James Demmel, Kurt Keutzer, Cho-Jui Hsieh
2019	A	`conf`	Large-batch training for LSTM and beyond. SC Yang You, Jonathan Hseu, Chris Ying, James Demmel, Kurt Keutzer, Cho-Jui Hsieh
2019	J	`jnl`	Learning to Learn by Zeroth-Order Oracle. CoRR Yangjun Ruan, Yuanhao Xiong, Sashank J. Reddi, Sanjiv Kumar, Cho-Jui Hsieh
2019	—	`conf`	Learning to Screen for Fast Softmax Inference on Large Vocabulary Neural Networks. ICLR (Poster) Patrick H. Chen, Si Si, Sanjiv Kumar, Yang Li, Cho-Jui Hsieh
2019	J	`jnl`	ML-LOO: Detecting Adversarial Examples with Feature Attribution. CoRR Puyudi Yang, Jianbo Chen, Cho-Jui Hsieh, Jane-Ling Wang, Michael I. Jordan
2019	—	`conf`	MulCode: A Multiplicative Multi-way Model for Compressing Neural Language Model. EMNLP/IJCNLP (1) Yukun Ma, Patrick H. Chen, Cho-Jui Hsieh
2019	J	`jnl`	Natural Adversarial Sentence Generation with Gradient-based Perturbation. CoRR Yu-Lun Hsieh, Minhao Cheng, Da-Cheng Juan, Wei Wei, Wen-Lian Hsu, Cho-Jui Hsieh
2019	J	`jnl`	Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise. CoRR Xuanqing Liu, Tesi Xiao, Si Si, Qin Cao, Sanjiv Kumar, Cho-Jui Hsieh
2019	—	`conf`	On the Robustness of Self-Attentive Models. ACL (1) Yu-Lun Hsieh, Minhao Cheng, Da-Cheng Juan, Wei Wei, Wen-Lian Hsu, Cho-Jui Hsieh
2019	J	`jnl`	Overcoming Catastrophic Forgetting by Generative Regularization. CoRR Patrick H. Chen, Wei Wei, Cho-Jui Hsieh, Bo Dai
2019	A	`conf`	Parallel Asynchronous Stochastic Coordinate Descent with Auxiliary Variables. AISTATS Hsiang-Fu Yu, Cho-Jui Hsieh, Inderjit S. Dhillon
2019	—	`conf`	Query-Efficient Hard-label Black-box Attack: An Optimization-based Approach. ICLR (Poster) Minhao Cheng, Thong Le, Pin-Yu Chen, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh
2019	A*	`conf`	RecurJac: An Efficient Recursive Algorithm for Bounding Jacobian Matrix of Neural Networks and Its Applications. AAAI Huan Zhang, Pengchuan Zhang, Cho-Jui Hsieh
2019	J	`jnl`	RedSync: Reducing synchronization bandwidth for distributed deep learning training system. J. Parallel Distributed Comput. Jiarui Fang, Haohuan Fu, Guangwen Yang, Cho-Jui Hsieh
2019	J	`jnl`	Reducing BERT Pre-Training Time from 3 Days to 76 Minutes. CoRR Yang You, Jing Li, Jonathan Hseu, Xiaodan Song, James Demmel, Cho-Jui Hsieh
2019	A*	`conf`	Rob-GAN: Generator, Discriminator, and Adversarial Attacker. CVPR Xuanqing Liu, Cho-Jui Hsieh
2019	A*	`conf`	Robust Decision Trees Against Adversarial Examples. ICML Hongge Chen, Huan Zhang, Duane S. Boning, Cho-Jui Hsieh
2019	J	`jnl`	Robust Decision Trees Against Adversarial Examples. CoRR Hongge Chen, Huan Zhang, Duane S. Boning, Cho-Jui Hsieh
2019	A*	`conf`	Robustness Verification of Tree-based Models. NeurIPS Hongge Chen, Huan Zhang, Si Si, Yang Li, Duane S. Boning, Cho-Jui Hsieh
2019	J	`jnl`	Robustness Verification of Tree-based Models. CoRR Hongge Chen, Huan Zhang, Si Si, Yang Li, Duane S. Boning, Cho-Jui Hsieh
2019	J	`jnl`	Sign-OPT: A Query-Efficient Hard-label Adversarial Attack. CoRR Minhao Cheng, Simranjit Singh, Patrick H. Chen, Pin-Yu Chen, Sijia Liu, Cho-Jui Hsieh
2019	A*	`conf`	Stochastic Shared Embeddings: Data-driven Regularization of Embedding Layers. NeurIPS Liwei Wu, Shuqing Li, Cho-Jui Hsieh, James L. Sharpnack
2019	J	`jnl`	Stochastic Shared Embeddings: Data-driven Regularization of Embedding Layers. CoRR Liwei Wu, Shuqing Li, Cho-Jui Hsieh, James Sharpnack
2019	J	`jnl`	Temporal Collaborative Ranking Via Personalized Transformer. CoRR Liwei Wu, Shuqing Li, Cho-Jui Hsieh, James Sharpnack
2019	—	`conf`	The Limitations of Adversarial Training and the Blind-Spot Attack. ICLR (Poster) Huan Zhang, Hongge Chen, Zhao Song, Duane S. Boning, Inderjit S. Dhillon, Cho-Jui Hsieh
2019	J	`jnl`	The Limitations of Adversarial Training and the Blind-Spot Attack. CoRR Huan Zhang, Hongge Chen, Zhao Song, Duane S. Boning, Inderjit S. Dhillon, Cho-Jui Hsieh
2019	J	`jnl`	Towards Stable and Efficient Training of Verifiably Robust Neural Networks. CoRR Huan Zhang, Hongge Chen, Chaowei Xiao, Bo Li, Duane S. Boning, Cho-Jui Hsieh
2019	J	`jnl`	VisualBERT: A Simple and Performant Baseline for Vision and Language. CoRR Liunian Harold Li, Mark Yatskar, Da Yin, Cho-Jui Hsieh, Kai-Wei Chang
2018	A	`conf`	Accurate, Fast and Scalable Kernel Ridge Regression on Parallel and Distributed Systems. ICS Yang You, James Demmel, Cho-Jui Hsieh, Richard W. Vuduc
2018	J	`jnl`	Accurate, Fast and Scalable Kernel Ridge Regression on Parallel and Distributed Systems. CoRR Yang You, James Demmel, Cho-Jui Hsieh, Richard W. Vuduc
2018	J	`jnl`	Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network. CoRR Xuanqing Liu, Yao Li, Chongruo Wu, Cho-Jui Hsieh
2018	J	`jnl`	Attack Graph Convolutional Networks by Adding Fake Nodes. CoRR Xiaoyun Wang, Joe Eaton, Cho-Jui Hsieh, Shyhtsun Felix Wu
2018	—	`conf`	Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning. ACL (1) Hongge Chen, Huan Zhang, Pin-Yu Chen, Jinfeng Yi, Cho-Jui Hsieh
2018	J	`jnl`	AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks. CoRR Chun-Chen Tu, Pai-Shun Ting, Pin-Yu Chen, Sijia Liu, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, Shin-Ming Cheng
2018	J	`jnl`	Block-wise Partitioning for Extreme Multi-label Classification. CoRR Yuefeng Liang, Cho-Jui Hsieh, Thomas C. M. Lee
2018	A*	`conf`	Distributed Primal-Dual Optimization for Non-uniformly Distributed Data. IJCAI Minhao Cheng, Cho-Jui Hsieh
2018	A*	`conf`	EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples. AAAI Pin-Yu Chen, Yash Sharma, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh
2018	A*	`conf`	Efficient Neural Network Robustness Certification with General Activation Functions. NeurIPS Huan Zhang, Tsui-Wei Weng, Pin-Yu Chen, Cho-Jui Hsieh, Luca Daniel
2018	J	`jnl`	Efficient Neural Network Robustness Certification with General Activation Functions. CoRR Huan Zhang, Tsui-Wei Weng, Pin-Yu Chen, Cho-Jui Hsieh, Luca Daniel
2018	—	`conf`	Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach. ICLR (Poster) Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen, Jinfeng Yi, Dong Su, Yupeng Gao, Cho-Jui Hsieh, Luca Daniel
2018	J	`jnl`	Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach. CoRR Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen, Jinfeng Yi, Dong Su, Yupeng Gao, Cho-Jui Hsieh, Luca Daniel
2018	A*	`conf`	Extreme Learning to Rank via Low Rank Assumption. ICML Minhao Cheng, Ian Davidson, Cho-Jui Hsieh
2018	A*	`conf`	Fast Variance Reduction Method with Stochastic Batch Size. ICML Xuanqing Liu, Cho-Jui Hsieh
2018	J	`jnl`	Fast Variance Reduction Method with Stochastic Batch Size. CoRR Xuanqing Liu, Cho-Jui Hsieh
2018	J	`jnl`	From Adversarial Training to Generative Adversarial Networks. CoRR Xuanqing Liu, Cho-Jui Hsieh
2018	J	`jnl`	Greedy Attack and Gumbel Attack: Generating Adversarial Examples for Discrete Data. CoRR Puyudi Yang, Jianbo Chen, Cho-Jui Hsieh, Jane-Ling Wang, Michael I. Jordan
2018	A*	`conf`	GroupReduce: Block-Wise Low-Rank Approximation for Neural Language Model Shrinking. NeurIPS Patrick H. Chen, Si Si, Yang Li, Ciprian Chelba, Cho-Jui Hsieh
2018	J	`jnl`	GroupReduce: Block-Wise Low-Rank Approximation for Neural Language Model Shrinking. CoRR Patrick H. Chen, Si Si, Yang Li, Ciprian Chelba, Cho-Jui Hsieh
2018	B	`conf`	ImageNet Training in Minutes. ICPP Yang You, Zhao Zhang, Cho-Jui Hsieh, James Demmel, Kurt Keutzer
2018	—	`conf`	Learning Word Embeddings for Low-Resource Languages by PU Learning. NAACL-HLT Chao Jiang, Hsiang-Fu Yu, Cho-Jui Hsieh, Kai-Wei Chang
2018	A*	`conf`	Learning from Group Comparisons: Exploiting Higher Order Interactions. NeurIPS Yao Li, Minhao Cheng, Kevin Fujii, Fushing Hsieh, Cho-Jui Hsieh
2018	J	`jnl`	Learning to Screen for Fast Softmax Inference on Large Vocabulary Neural Networks. CoRR Patrick H. Chen, Si Si, Sanjiv Kumar, Yang Li, Cho-Jui Hsieh
2018	J	`jnl`	LearningWord Embeddings for Low-resource Languages by PU Learning. CoRR Chao Jiang, Hsiang-Fu Yu, Cho-Jui Hsieh, Kai-Wei Chang
2018	—	`conf`	Multiple Accounts Detection on Facebook Using Semi-Supervised Learning on Graphs. MILCOM Xiaoyun Wang, Chun-Ming Lai, Yu-Cheng Lin, Cho-Jui Hsieh, Shyhtsun Felix Wu, Hasan Cam
2018	J	`jnl`	Multiple Accounts Detection on Facebook Using Semi-Supervised Learning on Graphs. CoRR Xiaoyun Wang, Chun-Ming Lai, Yunfeng Hong, Cho-Jui Hsieh, Shyhtsun Felix Wu
2018	A	`conf`	NLRR++: Scalable Subspace Clustering via Non-Convex Block Coordinate Descent. SDM Jun Wang, Cho-Jui Hsieh, Daming Shi
2018	J	`jnl`	On Extensions of CLEVER: A Neural Network Robustness Evaluation Algorithm. CoRR Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen, Aurélie C. Lozano, Cho-Jui Hsieh, Luca Daniel
2018	—	`conf`	On Extensions of Clever: A Neural Network Robustness Evaluation Algorithm. GlobalSIP Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen, Aurélie C. Lozano, Cho-Jui Hsieh, Luca Daniel
2018	J	`jnl`	Optimal Transport Classifier: Defending Against Adversarial Attacks by Regularized Deep Embedding. CoRR Yao Li, Martin Renqiang Min, Wenchao Yu, Cho-Jui Hsieh, Thomas C. M. Lee, Erik Kruus
2018	J	`jnl`	Query-Efficient Hard-label Black-box Attack: An Optimization-based Approach. CoRR Minhao Cheng, Thong Le, Pin-Yu Chen, Jinfeng Yi, Huan Zhang, Cho-Jui Hsieh
2018	J	`jnl`	RecurJac: An Efficient Recursive Algorithm for Bounding Jacobian Matrix of Neural Networks and Its Applications. CoRR Huan Zhang, Pengchuan Zhang, Cho-Jui Hsieh
2018	A*	`conf`	SQL-Rank: A Listwise Approach to Collaborative Ranking. ICML Liwei Wu, Cho-Jui Hsieh, James Sharpnack
2018	J	`jnl`	SQL-Rank: A Listwise Approach to Collaborative Ranking. CoRR Liwei Wu, Cho-Jui Hsieh, James Sharpnack
2018	J	`jnl`	Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples. CoRR Minhao Cheng, Jinfeng Yi, Huan Zhang, Pin-Yu Chen, Cho-Jui Hsieh
2018	J	`jnl`	Stochastic Second-order Methods for Non-convex Optimization with Inexact Hessian and Gradient. CoRR Liu Liu, Xuanqing Liu, Cho-Jui Hsieh, Dacheng Tao
2018	J	`jnl`	Stochastic Zeroth-order Optimization via Variance Reduction method. CoRR Liu Liu, Minhao Cheng, Cho-Jui Hsieh, Dacheng Tao
2018	J	`jnl`	Stochastically Controlled Stochastic Gradient for the Convex and Non-convex Composition problem. CoRR Liu Liu, Ji Liu, Cho-Jui Hsieh, Dacheng Tao
2018	A*	`conf`	Towards Fast Computation of Certified Robustness for ReLU Networks. ICML Tsui-Wei Weng, Huan Zhang, Hongge Chen, Zhao Song, Cho-Jui Hsieh, Luca Daniel, Duane S. Boning, Inderjit S. Dhillon
2018	J	`jnl`	Towards Fast Computation of Certified Robustness for ReLU Networks. CoRR Tsui-Wei Weng, Huan Zhang, Hongge Chen, Zhao Song, Cho-Jui Hsieh, Duane S. Boning, Inderjit S. Dhillon, Luca Daniel
2018	—	`conf`	Towards Robust Neural Networks via Random Self-ensemble. ECCV (7) Xuanqing Liu, Minhao Cheng, Huan Zhang, Cho-Jui Hsieh
2018	J	`jnl`	Using Side Information to Reliably Learn Low-Rank Matrices from Missing and Corrupted Observations. J. Mach. Learn. Res. Kai-Yang Chiang, Inderjit S. Dhillon, Cho-Jui Hsieh
2017	J	`jnl`	100-epoch ImageNet Training with AlexNet in 24 Minutes. CoRR Yang You, Zhao Zhang, Cho-Jui Hsieh, James Demmel
2017	—	`conf`	A Greedy Approach for Budgeted Maximum Inner Product Search. NIPS Hsiang-Fu Yu, Cho-Jui Hsieh, Qi Lei, Inderjit S. Dhillon
2017	A*	`conf`	A Hyperplane-Based Algorithm for Semi-Supervised Dimension Reduction. ICDM Huang Fang, Minhao Cheng, Cho-Jui Hsieh
2017	J	`jnl`	An inexact subsampled proximal Newton-type method for large-scale machine learning. CoRR Xuanqing Liu, Cho-Jui Hsieh, Jason D. Lee, Yuekai Sun
2017	—	`conf`	Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent. NIPS Xiangru Lian, Ce Zhang, Huan Zhang, Cho-Jui Hsieh, Wei Zhang, Ji Liu
2017	J	`jnl`	Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent. CoRR Xiangru Lian, Ce Zhang, Huan Zhang, Cho-Jui Hsieh, Wei Zhang, Ji Liu
2017	A*	`conf`	Communication-Efficient Distributed Block Minimization for Nonlinear Kernel Machines. KDD Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon
2017	C	`conf`	Computable Expert Knowledge in Computer Games. ICMLA Kevin Fujii, Fushing Hsieh, Cho-Jui Hsieh
2017	J	`jnl`	EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples. CoRR Pin-Yu Chen, Yash Sharma, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh
2017	J	`jnl`	GPU-acceleration for Large-scale Tree Boosting. CoRR Huan Zhang, Si Si, Cho-Jui Hsieh
2017	A*	`conf`	Gradient Boosted Decision Trees for High Dimensional Sparse Output. ICML Si Si, Huan Zhang, S. Sathiya Keerthi, Dhruv Mahajan, Inderjit S. Dhillon, Cho-Jui Hsieh
2017	A*	`conf`	Improved Bounded Matrix Completion for Large-Scale Recommender Systems. IJCAI Huang Fang, Zhen Zhang, Yiqun Shao, Cho-Jui Hsieh
2017	A*	`conf`	Large-scale Collaborative Ranking in Near-Linear Time. KDD Liwei Wu, Cho-Jui Hsieh, James Sharpnack
2017	J	`jnl`	Memory Efficient Kernel Approximation. J. Mach. Learn. Res. Si Si, Cho-Jui Hsieh, Inderjit S. Dhillon
2017	J	`jnl`	Positive-Unlabeled Demand-Aware Recommendation. CoRR Jinfeng Yi, Cho-Jui Hsieh, Kush R. Varshney, Lijun Zhang, Yao Li
2017	A	`conf`	Rank Aggregation and Prediction with Item Features. AISTATS Kai-Yang Chiang, Cho-Jui Hsieh, Inderjit S. Dhillon
2017	—	`conf`	Scalable Demand-Aware Recommendation. NIPS Jinfeng Yi, Cho-Jui Hsieh, Kush R. Varshney, Lijun Zhang, Yao Li
2017	J	`jnl`	Show-and-Fool: Crafting Adversarial Examples for Neural Image Captioning. CoRR Hongge Chen, Huan Zhang, Pin-Yu Chen, Jinfeng Yi, Cho-Jui Hsieh
2017	J	`jnl`	Towards Robust Neural Networks via Random Self-ensemble. CoRR Xuanqing Liu, Minhao Cheng, Huan Zhang, Cho-Jui Hsieh
2017	—	`conf`	ZOO: Zeroth Order Optimization Based Black-box Attacks to Deep Neural Networks without Training Substitute Models. AISec@CCS Pin-Yu Chen, Huan Zhang, Yash Sharma, Jinfeng Yi, Cho-Jui Hsieh
2017	J	`jnl`	ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute Models. CoRR Pin-Yu Chen, Huan Zhang, Yash Sharma, Jinfeng Yi, Cho-Jui Hsieh
2016	—	`conf`	A Comprehensive Linear Speedup Analysis for Asynchronous Stochastic Parallel Optimization from Zeroth-Order to First-Order. NIPS Xiangru Lian, Huan Zhang, Cho-Jui Hsieh, Yijun Huang, Ji Liu
2016	J	`jnl`	A Greedy Approach for Budgeted Maximum Inner Product Search. CoRR Hsiang-Fu Yu, Cho-Jui Hsieh, Qi Lei, Inderjit S. Dhillon
2016	—	`conf`	Asynchronous Parallel Greedy Coordinate Descent. NIPS Yang You, Xiangru Lian, Ji Liu, Hsiang-Fu Yu, Inderjit S. Dhillon, James Demmel, Cho-Jui Hsieh
2016	J	`jnl`	Communication-Efficient Parallel Block Minimization for Kernel Machines. CoRR Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon
2016	A*	`conf`	Computationally Efficient Nyström Approximation using Fast Transforms. ICML Si Si, Cho-Jui Hsieh, Inderjit S. Dhillon
2016	A*	`conf`	Fixing the Convergence Problems in Parallel Asynchronous Dual Coordinate Descent. ICDM Huan Zhang, Cho-Jui Hsieh
2016	A*	`conf`	Goal-Directed Inductive Matrix Completion. KDD Si Si, Kai-Yang Chiang, Cho-Jui Hsieh, Nikhil Rao, Inderjit S. Dhillon
2016	A*	`conf`	HogWild++: A New Mechanism for Decentralized Asynchronous Stochastic Gradient Descent. ICDM Huan Zhang, Cho-Jui Hsieh, Venkatesh Akella
2016	J	`jnl`	Machine Learning Meliorates Computing and Robustness in Discrete Combinatorial Optimization Problems. Frontiers Appl. Math. Stat. Fushing Hsieh, Kevin Fujii, Cho-Jui Hsieh
2016	J	`jnl`	Nomadic Computing for Big Data Analytics. Computer Hsiang-Fu Yu, Cho-Jui Hsieh, Hyokun Yun, S. V. N. Vishwanathan, Inderjit S. Dhillon
2016	A*	`conf`	Robust Principal Component Analysis with Side Information. ICML Kai-Yang Chiang, Cho-Jui Hsieh, Inderjit S. Dhillon
2015	A*	`conf`	A Scalable Asynchronous Distributed Algorithm for Topic Modeling. WWW Hsiang-Fu Yu, Cho-Jui Hsieh, Hyokun Yun, S. V. N. Vishwanathan, Inderjit S. Dhillon
2015	—	`conf`	Matrix Completion with Noisy Side Information. NIPS Kai-Yang Chiang, Cho-Jui Hsieh, Inderjit S. Dhillon
2015	A*	`conf`	PASSCoDe: Parallel ASynchronous Stochastic dual Co-ordinate Descent. ICML Cho-Jui Hsieh, Hsiang-Fu Yu, Inderjit S. Dhillon
2015	J	`jnl`	PASSCoDe: Parallel ASynchronous Stochastic dual Co-ordinate Descent. CoRR Cho-Jui Hsieh, Hsiang-Fu Yu, Inderjit S. Dhillon
2015	A*	`conf`	PU Learning for Matrix Completion. ICML Cho-Jui Hsieh, Nagarajan Natarajan, Inderjit S. Dhillon
2015	—	`conf`	Sparse Linear Programming via Primal and Dual Augmented Coordinate Descent. NIPS Ian En-Hsu Yen, Kai Zhong, Cho-Jui Hsieh, Pradeep Ravikumar, Inderjit S. Dhillon
2014	A*	`conf`	A Divide-and-Conquer Solver for Kernel Support Vector Machines. ICML Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon
2014	J	`jnl`	A Scalable Asynchronous Distributed Algorithm for Topic Modeling. CoRR Hsiang-Fu Yu, Cho-Jui Hsieh, Hyokun Yun, S. V. N. Vishwanathan, Inderjit S. Dhillon
2014	—	`conf`	Constant Nullspace Strong Convexity and Fast Convergence of Proximal Methods under High-Dimensional Settings. NIPS Ian En-Hsu Yen, Cho-Jui Hsieh, Pradeep Ravikumar, Inderjit S. Dhillon
2014	—	`conf`	Fast Prediction for Large-Scale Kernel Machines. NIPS Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon
2014	A*	`conf`	Memory Efficient Kernel Approximation. ICML Si Si, Cho-Jui Hsieh, Inderjit S. Dhillon
2014	J	`jnl`	NOMAD: Nonlocking, stOchastic Multi-machine algorithm for Asynchronous and Decentralized matrix completion. Proc. VLDB Endow. Hyokun Yun, Hsiang-Fu Yu, Cho-Jui Hsieh, S. V. N. Vishwanathan, Inderjit S. Dhillon
2014	A*	`conf`	Nuclear Norm Minimization via Active Subspace Selection. ICML Cho-Jui Hsieh, Peder A. Olsen
2014	J	`jnl`	PU Learning for Matrix Completion. CoRR Cho-Jui Hsieh, Nagarajan Natarajan, Inderjit S. Dhillon
2014	J	`jnl`	Parallel matrix factorization for recommender systems. Knowl. Inf. Syst. Hsiang-Fu Yu, Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon
2014	J	`jnl`	Prediction and clustering in signed networks: a local to global perspective. J. Mach. Learn. Res. Kai-Yang Chiang, Cho-Jui Hsieh, Nagarajan Natarajan, Inderjit S. Dhillon, Ambuj Tewari
2014	—	`conf`	QUIC & DIRTY: A Quadratic Approximation Approach for Dirty Statistical Models. NIPS Cho-Jui Hsieh, Inderjit S. Dhillon, Pradeep Ravikumar, Stephen Becker, Peder A. Olsen
2014	J	`jnl`	QUIC: quadratic approximation for sparse inverse covariance estimation. J. Mach. Learn. Res. Cho-Jui Hsieh, Mátyás A. Sustik, Inderjit S. Dhillon, Pradeep Ravikumar
2013	J	`jnl`	A Divide-and-Conquer Solver for Kernel Support Vector Machines. CoRR Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon
2013	—	`conf`	BIG & QUIC: Sparse Inverse Covariance Estimation for a Million Variables. NIPS Cho-Jui Hsieh, Mátyás A. Sustik, Inderjit S. Dhillon, Pradeep Ravikumar, Russell A. Poldrack
2013	—	`conf`	Large Scale Distributed Sparse Precision Estimation. NIPS Huahua Wang, Arindam Banerjee, Cho-Jui Hsieh, Pradeep Ravikumar, Inderjit S. Dhillon
2013	J	`jnl`	NOMAD: Non-locking, stOchastic Multi-machine algorithm for Asynchronous and Decentralized matrix completion. CoRR Hyokun Yun, Hsiang-Fu Yu, Cho-Jui Hsieh, S. V. N. Vishwanathan, Inderjit S. Dhillon
2013	A*	`conf`	Organizational overlap on social networks and its applications. WWW Cho-Jui Hsieh, Mitul Tiwari, Deepak Agarwal, Xinyi (Lisa) Huang, Sam Shah
2013	J	`jnl`	Prediction and Clustering in Signed Networks: A Local to Global Perspective CoRR Kai-Yang Chiang, Cho-Jui Hsieh, Nagarajan Natarajan, Ambuj Tewari, Inderjit S. Dhillon
2013	J	`jnl`	Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation. CoRR Cho-Jui Hsieh, Mátyás A. Sustik, Inderjit S. Dhillon, Pradeep Ravikumar
2012	—	`conf`	A Divide-and-Conquer Method for Sparse Inverse Covariance Estimation. NIPS Cho-Jui Hsieh, Inderjit S. Dhillon, Pradeep Ravikumar, Arindam Banerjee
2012	J	`jnl`	Large Linear Classification When Data Cannot Fit in Memory. ACM Trans. Knowl. Discov. Data Hsiang-Fu Yu, Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin
2012	A*	`conf`	Low rank modeling of signed networks. KDD Cho-Jui Hsieh, Kai-Yang Chiang, Inderjit S. Dhillon
2012	A*	`conf`	Scalable Coordinate Descent Approaches to Parallel Matrix Factorization for Recommender Systems. ICDM Hsiang-Fu Yu, Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon
2012	—	`conf`	Sparse inverse covariance matrix estimation using quadratic approximation. MLSLP Inderjit S. Dhillon, Cho-Jui Hsieh, Mátyás A. Sustik, Pradeep Ravikumar
2011	A*	`conf`	Fast coordinate descent methods with variable selection for non-negative matrix factorization. KDD Cho-Jui Hsieh, Inderjit S. Dhillon
2011	A*	`conf`	Large Linear Classification When Data Cannot Fit in Memory. IJCAI Hsiang-Fu Yu, Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin
2011	—	`conf`	Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation. NIPS Cho-Jui Hsieh, Mátyás A. Sustik, Inderjit S. Dhillon, Pradeep Ravikumar
2010	J	`jnl`	A Comparison of Optimization Methods and Software for Large-scale L1-regularized Linear Classification. J. Mach. Learn. Res. Guo-Xun Yuan, Kai-Wei Chang, Cho-Jui Hsieh, Chih-Jen Lin
2010	J	`jnl`	Iterative Scaling and Coordinate Descent Methods for Maximum Entropy Models J. Mach. Learn. Res. Fang-Lan Huang, Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin
2010	A*	`conf`	Large linear classification when data cannot fit in memory. KDD Hsiang-Fu Yu, Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin
2010	J	`jnl`	Training and Testing Low-degree Polynomial Data Mappings via Linear SVM. J. Mach. Learn. Res. Yin-Wen Chang, Cho-Jui Hsieh, Kai-Wei Chang, Michael Ringgaard, Chih-Jen Lin
2009	—	`conf`	An Ensemble of Three Classifiers for KDD Cup 2009: Expanded Linear Model, Heterogeneous Boosting, and Selective Naive Bayes. KDD Cup Hung-Yi Lo, Kai-Wei Chang, Shang-Tse Chen, Tsung-Hsien Chiang, Chun-Sung Ferng, Cho-Jui Hsieh, Yi-Kuang Ko, Tsung-Ting Kuo, Hung-Che Lai, Ken-Yi Lin, Chia-Hsuan Wang, Hsiang-Fu Yu, Chih-Jen Lin, Hsuan-Tien Lin, Shou-De Lin
2009	—	`conf`	Iterative Scaling and Coordinate Descent Methods for Maximum Entropy. ACL/IJCNLP (2) Fang-Lan Huang, Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin
2008	A*	`conf`	A dual coordinate descent method for large-scale linear SVM. ICML Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin, S. Sathiya Keerthi, S. Sundararajan
2008	A*	`conf`	A sequential dual method for large scale multi-class linear svms. KDD S. Sathiya Keerthi, S. Sundararajan, Kai-Wei Chang, Cho-Jui Hsieh, Chih-Jen Lin
2008	J	`jnl`	Coordinate Descent Method for Large-scale L2-loss Linear Support Vector Machines. J. Mach. Learn. Res. Kai-Wei Chang, Cho-Jui Hsieh, Chih-Jen Lin
2008	J	`jnl`	LIBLINEAR: A Library for Large Linear Classification. J. Mach. Learn. Res. Rong-En Fan, Kai-Wei Chang, Cho-Jui Hsieh, Xiang-Rui Wang, Chih-Jen Lin