Zhang, Huan

95 publications

ICLR 2026 BEAT: Visual Backdoor Attacks on VLM-Based Embodied Agents via Contrastive Trigger Learning Qiusi Zhan, Hyeonjeong Ha, Rui Yang, Sirui Xu, Hanyang Chen, Liangyan Gui, Yu-Xiong Wang, Huan Zhang, Heng Ji, Daniel Kang

ICLR 2026 DR-SAC: Distributionally Robust Soft Actor-Critic for Reinforcement Learning Under Uncertainty Mingxuan Cui, Duo Zhou, Yuxuan Han, Grani A. Hanasusanto, Qiong Wang, Huan Zhang, Zhengyuan Zhou

ICLR 2026 On the Fragility of Benchmark Contamination Detection in Reasoning Models Han Wang, Haoyu Li, Brian Ko, Huan Zhang

ICLR 2026 TokUR: Token-Level Uncertainty Estimation for Large Language Model Reasoning Tunyu Zhang, Haizhou Shi, Yibin Wang, Hengyi Wang, Xiaoxiao He, Zhuowei Li, Haoxian Chen, Ligong Han, Kai Xu, Huan Zhang, Dimitris N. Metaxas, Hao Wang

ICLR 2026 TrustGen: A Platform of Dynamic Benchmarking on the Trustworthiness of Generative Foundation Models Yue Huang, Chujie Gao, Siyuan Wu, Haoran Wang, Xiangqi Wang, Jiayi Ye, Yujun Zhou, Yanbo Wang, Jiawen Shi, Qihui Zhang, Han Bao, Zhaoyi Liu, Yuan Li, Tianrui Guan, Peiran Wang, Haomin Zhuang, Dongping Chen, Kehan Guo, Andy Zou, Bryan Hooi, Caiming Xiong, Elias Stengel-Eskin, Hongyang Zhang, Hongzhi Yin, Huan Zhang, Huaxiu Yao, Jieyu Zhang, Jaehong Yoon, Kai Shu, Ranjay Krishna, Swabha Swayamdipta, Weijia Shi, Xiang Li, Yuexing Hao, Zhihao Jia, Zhize Li, Xiuying Chen, Zhengzhong Tu, Xiyang Hu, Tianyi Zhou, Jieyu Zhao, Lichao Sun, Furong Huang, Or Cohen-Sasson, Prasanna Sattigeri, Anka Reuel, Max Lamparth, Yue Zhao, Nouha Dziri, Yu Su, Huan Sun, Heng Ji, Chaowei Xiao, Mohit Bansal, Nitesh V Chawla, Jian Pei, Jianfeng Gao, Michael Backes, Philip S. Yu, Neil Zhenqiang Gong, Pin-Yu Chen, Bo Li, Dawn Song, Xiangliang Zhang

NeurIPS 2025 Abstract Rendering: Certified Rendering Under 3D Semantic Uncertainty Chenxi Ji, Yangge Li, Xiangru Zhong, Huan Zhang, Sayan Mitra

ICLR 2025 BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Keyi Shen, Jiangwei Yu, Jose Barreiros, Huan Zhang, Yunzhu Li

NeurIPS 2025 CLIP-and-Verify: Linear Constraint-Driven Domain Clipping for Accelerating Neural Network Verification Duo Zhou, Jorge Chavez, Hesun Chen, Grani A. Hanasusanto, Huan Zhang

CVPR 2025 Causal Composition Diffusion Model for Closed-Loop Traffic Generation Haohong Lin, Xin Huang, Tung Phan, David Hayden, Huan Zhang, Ding Zhao, Siddhartha Srinivasa, Eric Wolff, Hongge Chen

ICLR 2025 DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models Chengke Zou, Xingang Guo, Rui Yang, Junyu Zhang, Bin Hu, Huan Zhang

ICML 2025 EmbodiedBench: Comprehensive Benchmarking Multi-Modal Large Language Models for Vision-Driven Embodied Agents 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

NeurIPS 2025 GUI-Actor: Coordinate-Free Visual Grounding for GUI Agents 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

NeurIPS 2025 Improving Data Efficiency for LLM Reinforcement Fine-Tuning Through Difficulty-Targeted Online Data Selection and Rollout Replay Yifan Sun, Jingyan Shen, Yibin Wang, Tianyu Chen, Zhendong Wang, Mingyuan Zhou, Huan Zhang

ICML 2025 Instance Correlation Graph-Based Naive Bayes Chengyuan Li, Liangxiao Jiang, Wenjun Zhang, Liangjun Yu, Huan Zhang

L4DC 2025 Neural Contraction Metrics with Formal Guarantees for Discrete-Time Nonlinear Dynamical Systems Haoyu Li, Xiangru Zhong, Bin Hu, Huan Zhang

JMLR 2025 PREMAP: A Unifying PREiMage APproximation Framework for Neural Networks Xiyue Zhang, Benjie Wang, Marta Kwiatkowska, Huan Zhang

TMLR 2025 Reliable and Responsible Foundation Models Xinyu Yang, Junlin Han, Rishi Bommasani, Jinqi Luo, Wenjie Qu, Wangchunshu Zhou, Adel Bibi, Xiyao Wang, Jaehong Yoon, Elias Stengel-Eskin, Shengbang Tong, Lingfeng Shen, Rafael Rafailov, Runjia Li, Zhaoyang Wang, Yiyang Zhou, Chenhang Cui, Yu Wang, Wenhao Zheng, Huichi Zhou, Jindong Gu, Zhaorun Chen, Peng Xia, Tony Lee, Thomas P Zollo, Vikash Sehwag, Jixuan Leng, Jiuhai Chen, Yuxin Wen, Huan Zhang, Zhun Deng, Linjun Zhang, Pavel Izmailov, Pang Wei Koh, Yulia Tsvetkov, Andrew Gordon Wilson, Jiaheng Zhang, James Zou, Cihang Xie, Hao Wang, Philip Torr, Julian McAuley, David Alvarez-Melis, Florian Tramèr, Kaidi Xu, Suman Jana, Chris Callison-Burch, Rene Vidal, Filippos Kokkinos, Mohit Bansal, Beidi Chen, Huaxiu Yao

ICML 2025 SDP-CROWN: Efficient Bound Propagation for Neural Network Verification with Tightness of Semidefinite Programming Hong-Ming Chiu, Hao Chen, Huan Zhang, Richard Y. Zhang

TMLR 2025 SoundnessBench: A Soundness Benchmark for Neural Network Verifiers Xingjian Zhou, Keyi Shen, Andy Xu, Hongji Xu, Cho-Jui Hsieh, Huan Zhang, Zhouxing Shi

CVPR 2025 Stealthy Backdoor Attack in Self-Supervised Learning Vision Encoders for Large Vision Language Models Zhaoyi Liu, Huan Zhang

CVPR 2025 Steering Away from Harm: An Adaptive Approach to Defending Vision Language Model Against Jailbreaks Han Wang, Gang Wang, Huan Zhang

ICLRW 2025 The Emperor's New Clothes in Benchmarking? a Rigorous Examination of Mitigation Strategies for LLM Benchmark Data Contamination Yifan Sun, Han Wang, Dongbai Li, Gang Wang, Huan Zhang

ICML 2025 The Emperor’s New Clothes in Benchmarking? a Rigorous Examination of Mitigation Strategies for LLM Benchmark Data Contamination Yifan Sun, Han Wang, Dongbai Li, Gang Wang, Huan Zhang

NeurIPS 2025 Toward Engineering AGI: Benchmarking the Engineering Design Capabilities of LLMs Xingang Guo, Yaxin Li, XiangYi Kong, Yilan Jiang, Xiayu Zhao, Zhihua Gong, Yufan Zhang, Daixuan Li, Tianle Sang, Beixiao Zhu, Gregory Jun, Yingbing Huang, Yiqi Liu, Yuqi Xue, Rahul Dev Kundu, Qi Jian Lim, Yizhou Zhao, Luke Alexander Granger, Mohamed Badr Younis, Darioush Keivan, Nippun Sabharwal, Shreyanka Sinha, Prakhar Agarwal, Kojo Vandyck, Hanlin Mai, Zichen Wang, Aditya Venkatesh, Ayush Barik, Jiankun Yang, Chongying Yue, Jingjie He, Libin Wang, Licheng Xu, Hao Chen, Jinwen Wang, Liujun Xu, Rushabh Shetty, Ziheng Guo, Dahui Song, Manvi Jha, Weijie Liang, Weiman Yan, Bryan Zhang, Sahil Bhandary Karnoor, Jialiang Zhang, Rutva Pandya, Xinyi Gong, Mithesh Ballae Ganesh, Feize Shi, Ruiling Xu, Yifan Zhang, Yanfeng Ouyang, Lianhui Qin, Elyse Rosenbaum, Corey Snyder, Peter Seiler, Geir Dullerud, Xiaojia Shelly Zhang, Zuofu Cheng, Pavan Kumar Hanumolu, Jian Huang, Mayank Kulkarni, Mahdi Namazifar, Huan Zhang, Bin Hu

NeurIPS 2025 Training-Free Bayesianization for Low-Rank Adapters of Large Language Models Haizhou Shi, Yibin Wang, Ligong Han, Huan Zhang, Hao Wang

ICLRW 2025 Training-Free Bayesianization for Low-Rank Adapters of Large Language Models Haizhou Shi, Yibin Wang, Ligong Han, Huan Zhang, Hao Wang

NeurIPS 2025 Two‑Stage Learning of Stabilizing Neural Controllers via Zubov Sampling and Iterative Domain Expansion Haoyu Li, Xiangru Zhong, Bin Hu, Huan Zhang

ICML 2024 COLD-Attack: Jailbreaking LLMs with Stealthiness and Controllability Xingang Guo, Fangxu Yu, Huan Zhang, Lianhui Qin, Bin Hu

ICML 2024 Fine-Grained Local Sensitivity Analysis of Standard Dot-Product Self-Attention Aaron J Havens, Alexandre Araujo, Huan Zhang, Bin Hu

NeurIPSW 2024 HoneyComb: A Flexible LLM-Based Agent System for Materials Science Huan Zhang, Yu Song, Ziyu Hou, Santiago Miret, Bang Liu

ICML 2024 Lyapunov-Stable Neural Control for State and Output Feedback: A Novel Formulation Lujie Yang, Hongkai Dai, Zhouxing Shi, Cho-Jui Hsieh, Russ Tedrake, Huan Zhang

NeurIPS 2024 NN4SysBench: Characterizing Neural Network Verification for Computer Systems Shuyi Lin, Haoyu He, Tianhao Wei, Kaidi Xu, Huan Zhang, Gagandeep Singh, Changliu Liu, Cheng Tan

ICML 2024 Position: TrustLLM: Trustworthiness in Large Language Models Yue Huang, Lichao Sun, Haoran Wang, Siyuan Wu, Qihui Zhang, Yuan Li, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Hanchi Sun, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bertie Vidgen, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, Joaquin Vanschoren, John Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Yang Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao

NeurIPS 2024 Regularizing Hidden States Enables Learning Generalizable Reward Model for LLMs Rui Yang, Ruomeng Ding, Yong Lin, Huan Zhang, Tong Zhang

NeurIPS 2024 Scalable Neural Network Verification with Branch-and-Bound Inferred Cutting Planes Duo Zhou, Christopher Brix, Grani A Hanasusanto, Huan Zhang

NeurIPS 2024 Verified Safe Reinforcement Learning for Neural Network Dynamic Models Junlin Wu, Huan Zhang, Yevgeniy Vorobeychik

ICLRW 2024 WavCraft: Audio Editing and Generation with Large Language Models Jinhua Liang, Huan Zhang, Haohe Liu, Yin Cao, Qiuqiang Kong, Xubo Liu, Wenwu Wang, Mark D Plumbley, Huy Phan, Emmanouil Benetos

ICLR 2023 Can Agents Run Relay Race with Strangers? Generalization of RL to Out-of-Distribution Trajectories Li-Cheng Lan, Huan Zhang, Cho-Jui Hsieh

NeurIPSW 2023 HoneyBee: Progressive Instruction Finetuning of Large Language Models for Materials Science Yu Song, Santiago Miret, Huan Zhang, Bang Liu

ICLR 2023 On the Robustness of Safe Reinforcement Learning Under Observational Perturbations Zuxin Liu, Zijian Guo, Zhepeng Cen, Huan Zhang, Jie Tan, Bo Li, Ding Zhao

NeurIPS 2023 Provably Bounding Neural Network Preimages Suhas Kotha, Christopher Brix, J. Zico Kolter, Krishnamurthy Dvijotham, Huan Zhang

ICCV 2023 Robust Mixture-of-Expert Training for Convolutional Neural Networks Yihua Zhang, Ruisi Cai, Tianlong Chen, Guanhua Zhang, Huan Zhang, Pin-Yu Chen, Shiyu Chang, Zhangyang Wang, Sijia Liu

ICML 2023 Towards Robust and Safe Reinforcement Learning with Benign Off-Policy Data Zuxin Liu, Zijian Guo, Zhepeng Cen, Huan Zhang, Yihang Yao, Hanjiang Hu, Ding Zhao

ICML 2022 A Branch and Bound Framework for Stronger Adversarial Attacks of ReLU Networks Huan Zhang, Shiqi Wang, Kaidi Xu, Yihan Wang, Suman Jana, Cho-Jui Hsieh, Zico Kolter

NeurIPS 2022 Are AlphaZero-like Agents Robust to Adversarial Perturbations? Li-Cheng Lan, Huan Zhang, Ti-Rong Wu, Meng-Yu Tsai, I-Chen Wu, Cho-Jui Hsieh

ICLR 2022 COPA: Certifying Robust Policies for Offline Reinforcement Learning Against Poisoning Attacks Fan Wu, Linyi Li, Huan Zhang, Bhavya Kailkhura, Krishnaram Kenthapadi, Ding Zhao, Bo Li

NeurIPSW 2022 Denoised Smoothing with Sample Rejection for Robustifying Pretrained Classifiers Fatemeh Sheikholeslami, Wan-Yi Lin, Jan Hendrik Metzen, Huan Zhang, J Zico Kolter

NeurIPS 2022 Efficiently Computing Local Lipschitz Constants of Neural Networks via Bound Propagation Zhouxing Shi, Yihan Wang, Huan Zhang, J. Zico Kolter, Cho-Jui Hsieh

NeurIPSW 2022 Evaluating Worst Case Adversarial Weather Perturbations Robustness Yihan Wang, Yunhao Ba, Howard Chenyang Zhang, Huan Zhang, Achuta Kadambi, Stefano Soatto, Alex Wong, Cho-Jui Hsieh

NeurIPS 2022 General Cutting Planes for Bound-Propagation-Based Neural Network Verification Huan Zhang, Shiqi Wang, Kaidi Xu, Linyi Li, Bo Li, Suman Jana, Cho-Jui Hsieh, J. Zico Kolter

ICML 2022 Linearity Grafting: Relaxed Neuron Pruning Helps Certifiable Robustness Tianlong Chen, Huan Zhang, Zhenyu Zhang, Shiyu Chang, Sijia Liu, Pin-Yu Chen, Zhangyang Wang

NeurIPSW 2022 On the Robustness of Safe Reinforcement Learning Under Observational Perturbations Zuxin Liu, Zijian Guo, Zhepeng Cen, Huan Zhang, Jie Tan, Bo Li, Ding Zhao

ECCV 2022 VIP: Unified Certified Detection and Recovery for Patch Attack with Vision Transformers Junbo Li, Huan Zhang, Cihang Xie

NeurIPS 2021 Beta-CROWN: Efficient Bound Propagation with Per-Neuron Split Constraints for Neural Network Robustness Verification Shiqi Wang, Huan Zhang, Kaidi Xu, Xue Lin, Suman Jana, Cho-Jui Hsieh, J. Zico Kolter

ICMLW 2021 Beta-CROWN: Efficient Bound Propagation with Per-Neuron Split Constraints for Neural Network Robustness Verification Shiqi Wang, Huan Zhang, Kaidi Xu, Xue Lin, Suman Jana, Cho-Jui Hsieh, J Zico Kolter

ICMLW 2021 Empirical Robustification of Pre-Trained Classifiers Mohammad Sadegh Norouzzadeh, Wan-Yi Lin, Leonid Boytsov, Leslie Rice, Huan Zhang, Filipe Condessa, J Zico Kolter

NeurIPS 2021 Fast Certified Robust Training with Short Warmup Zhouxing Shi, Yihan Wang, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh

ICMLW 2021 Fast Certified Robust Training with Short Warmup Zhouxing Shi, Yihan Wang, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh

ICLR 2021 Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers Kaidi Xu, Huan Zhang, Shiqi Wang, Yihan Wang, Suman Jana, Xue Lin, Cho-Jui Hsieh

JMLR 2021 LocalGAN: Modeling Local Distributions for Adversarial Response Generation Baoxun Wang, Zhen Xu, Huan Zhang, Kexin Qiu, Deyuan Zhang, Chengjie Sun

ICLR 2021 Robust Reinforcement Learning on State Observations with Learned Optimal Adversary Huan Zhang, Hongge Chen, Duane S Boning, Cho-Jui Hsieh

NeurIPS 2021 Robustness Between the Worst and Average Case Leslie Rice, Anna Bair, Huan Zhang, J. Zico Kolter

NeurIPS 2021 Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds Yujia Huang, Huan Zhang, Yuanyuan Shi, J. Zico Kolter, Anima Anandkumar

NeurIPS 2020 An Efficient Adversarial Attack for Tree Ensembles Chong Zhang, Huan Zhang, Cho-Jui Hsieh

NeurIPS 2020 Automatic Perturbation Analysis for Scalable Certified Robustness and Beyond Kaidi Xu, Zhouxing Shi, Huan Zhang, Yihan Wang, Kai-Wei Chang, Minlie Huang, Bhavya Kailkhura, Xue Lin, Cho-Jui Hsieh

ICLR 2020 MACER: Attack-Free and Scalable Robust Training via Maximizing Certified Radius Runtian Zhai, Chen Dan, Di He, Huan Zhang, Boqing Gong, Pradeep Ravikumar, Cho-Jui Hsieh, Liwei Wang

ICML 2020 On Lp-Norm Robustness of Ensemble Decision Stumps and Trees Yihan Wang, Huan Zhang, Hongge Chen, Duane Boning, Cho-Jui Hsieh

NeurIPS 2020 Robust Deep Reinforcement Learning Against Adversarial Perturbations on State Observations Huan Zhang, Hongge Chen, Chaowei Xiao, Bo Li, Mingyan Liu, Duane Boning, Cho-Jui Hsieh

ICLR 2020 Robustness Verification for Transformers Zhouxing Shi, Huan Zhang, Kai-Wei Chang, Minlie Huang, Cho-Jui Hsieh

AAAI 2020 Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples Minhao Cheng, Jinfeng Yi, Pin-Yu Chen, Huan Zhang, Cho-Jui Hsieh

MLJ 2020 Spanning Attack: Reinforce Black-Box Attacks with Unlabeled Data Lu Wang, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, Yuan Jiang

ICLR 2020 Towards Stable and Efficient Training of Verifiably Robust Neural Networks Huan Zhang, Hongge Chen, Chaowei Xiao, Sven Gowal, Robert Stanforth, Bo Li, Duane Boning, Cho-Jui Hsieh

NeurIPS 2019 A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks Hadi Salman, Greg Yang, Huan Zhang, Cho-Jui Hsieh, Pengchuan Zhang

ICCV 2019 Adversarial Robustness vs. Model Compression, or Both? Shaokai Ye, Kaidi Xu, Sijia Liu, Hao Cheng, Jan-Henrik Lambrechts, Huan Zhang, Aojun Zhou, Kaisheng Ma, Yanzhi Wang, Xue Lin

AAAI 2019 AutoZOOM: Autoencoder-Based Zeroth Order Optimization Method for Attacking Black-Box Neural Networks Chun-Chen Tu, Pai-Shun Ting, Pin-Yu Chen, Sijia Liu, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, Shin-Ming Cheng

CVPRW 2019 Defending Against Adversarial Attacks Using Random Forest Yifan Ding, Liqiang Wang, Huan Zhang, Jinfeng Yi, Deliang Fan, Boqing Gong

ICCV 2019 Evaluating Robustness of Deep Image Super-Resolution Against Adversarial Attacks Jun-Ho Choi, Huan Zhang, Jun-Hyuk Kim, Cho-Jui Hsieh, Jong-Seok Lee

ICLR 2019 Minimum Divergence vs. Maximum Margin: An Empirical Comparison on Seq2Seq Models Huan Zhang, Hai Zhao

NeurIPS 2019 Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers Hadi Salman, Jerry Li, Ilya Razenshteyn, Pengchuan Zhang, Huan Zhang, Sebastien Bubeck, Greg Yang

ICLR 2019 Query-Efficient Hard-Label Black-Box Attack: An Optimization-Based Approach Minhao Cheng, Thong Le, Pin-Yu Chen, Huan Zhang, JinFeng Yi, Cho-Jui Hsieh

AAAI 2019 RecurJac: An Efficient Recursive Algorithm for Bounding Jacobian Matrix of Neural Networks and Its Applications Huan Zhang, Pengchuan Zhang, Cho-Jui Hsieh

ICML 2019 Robust Decision Trees Against Adversarial Examples Hongge Chen, Huan Zhang, Duane Boning, Cho-Jui Hsieh

NeurIPS 2019 Robustness Verification of Tree-Based Models Hongge Chen, Huan Zhang, Si Si, Yang Li, Duane Boning, Cho-Jui Hsieh

ICLR 2019 Structured Adversarial Attack: Towards General Implementation and Better Interpretability Kaidi Xu, Sijia Liu, Pu Zhao, Pin-Yu Chen, Huan Zhang, Quanfu Fan, Deniz Erdogmus, Yanzhi Wang, Xue Lin

ICLR 2019 The Limitations of Adversarial Training and the Blind-Spot Attack Huan Zhang, Hongge Chen, Zhao Song, Duane Boning, Inderjit S. Dhillon, Cho-Jui Hsieh

AAAI 2018 EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples Pin-Yu Chen, Yash Sharma, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh

NeurIPS 2018 Efficient Neural Network Robustness Certification with General Activation Functions Huan Zhang, Tsui-Wei Weng, Pin-Yu Chen, Cho-Jui Hsieh, Luca Daniel

ICLR 2018 Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen, Jinfeng Yi, Dong Su, Yupeng Gao, Cho-Jui Hsieh, Luca Daniel

ECCV 2018 Is Robustness the Cost of Accuracy? -- a Comprehensive Study on the Robustness of 18 Deep Image Classification Models Dong Su, Huan Zhang, Hongge Chen, Jinfeng Yi, Pin-Yu Chen, Yupeng Gao

ICML 2018 Towards Fast Computation of Certified Robustness for ReLU Networks Lily Weng, Huan Zhang, Hongge Chen, Zhao Song, Cho-Jui Hsieh, Luca Daniel, Duane Boning, Inderjit Dhillon

ECCV 2018 Towards Robust Neural Networks via Random Self-Ensemble Xuanqing Liu, Minhao Cheng, Huan Zhang, Cho-Jui Hsieh

NeurIPS 2017 Can Decentralized Algorithms Outperform Centralized Algorithms? a Case Study for Decentralized Parallel Stochastic Gradient Descent Xiangru Lian, Ce Zhang, Huan Zhang, Cho-Jui Hsieh, Wei Zhang, Ji Liu

ICML 2017 Gradient Boosted Decision Trees for High Dimensional Sparse Output Si Si, Huan Zhang, S. Sathiya Keerthi, Dhruv Mahajan, Inderjit S. Dhillon, Cho-Jui Hsieh

NeurIPS 2016 A Comprehensive Linear Speedup Analysis for Asynchronous Stochastic Parallel Optimization from Zeroth-Order to First-Order Xiangru Lian, Huan Zhang, Cho-Jui Hsieh, Yijun Huang, Ji Liu

NeurIPS 2016 Sublinear Time Orthogonal Tensor Decomposition Zhao Song, David Woodruff, Huan Zhang