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ORCIDHuan Zhang 0001
Person information
- affiliation: Carnegie Mellon University (CMU), Department of Computer Science, Pittsburgh, PA, USA
- affiliation (former): University of California, Los Angeles, CA, USA
- affiliation (former): University of California, Davis, CA, USA
- affiliation (former): IBM T. J. Watson Research Center, Yorktown Heights, NY, USA
Other persons with the same name
- Huan Zhang — disambiguation page
- Huan Zhang 0002
![[0000-0001-8068-6636]](https://dblp.org/img/orcid-mark.12x12.png "0000-0001-8068-6636")
— Beijing University of Posts and Telecommunications, School of Cyberspace Security, China - Huan Zhang 0003 — Guizhou University, Key Laboratory of Advanced Manufacturing Technology, Guiyang, China
- Huan Zhang 0004 — Zhejiang University, Department of Instrument Science & Technology,
- Huan Zhang 0005 — Macau University of Science and Technology, Faculty of Information Technology, China
- Huan Zhang 0006 — Chinese Academy of Sciences, Institute of Electronics, Beijing, China
- Huan Zhang 0007 — China University of Geosciences, School of Computer Science, Wuhan, China
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2020 – today
- 2024
[j2]Jaehui Hwang, Huan Zhang, Jun-Ho Choi, Cho-Jui Hsieh, Jong-Seok Lee:
Temporal shuffling for defending deep action recognition models against adversarial attacks. Neural Networks 169: 388-397 (2024)- [i53]Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, John Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yue Zhao:
TrustLLM: Trustworthiness in Large Language Models. CoRR abs/2401.05561 (2024) - [i52]Lujie Yang, Hongkai Dai, Zhouxing Shi, Cho-Jui Hsieh, Russ Tedrake, Huan Zhang:
Lyapunov-stable Neural Control for State and Output Feedback: A Novel Formulation for Efficient Synthesis and Verification. CoRR abs/2404.07956 (2024) - 2023
- [c54]Yihua Zhang, Ruisi Cai, Tianlong Chen, Guanhua Zhang, Huan Zhang, Pin-Yu Chen, Shiyu Chang, Zhangyang Wang, Sijia Liu:
Robust Mixture-of-Expert Training for Convolutional Neural Networks. ICCV 2023: 90-101 - [c53]Li-Cheng Lan, Huan Zhang, Cho-Jui Hsieh:
Can Agents Run Relay Race with Strangers? Generalization of RL to Out-of-Distribution Trajectories. ICLR 2023 - [c52]Suhas Kotha, Christopher Brix, J. Zico Kolter, Krishnamurthy Dvijotham, Huan Zhang:
Provably Bounding Neural Network Preimages. NeurIPS 2023 - [i51]Suhas Kotha, Christopher Brix, Zico Kolter, Krishnamurthy Dvijotham, Huan Zhang:
Provably Bounding Neural Network Preimages. CoRR abs/2302.01404 (2023) - [i50]Li-Cheng Lan, Huan Zhang, Cho-Jui Hsieh:
Can Agents Run Relay Race with Strangers? Generalization of RL to Out-of-Distribution Trajectories. CoRR abs/2304.13424 (2023) - [i49]Yihua Zhang, Ruisi Cai, Tianlong Chen, Guanhua Zhang, Huan Zhang, Pin-Yu Chen, Shiyu Chang, Zhangyang Wang, Sijia Liu:
Robust Mixture-of-Expert Training for Convolutional Neural Networks. CoRR abs/2308.10110 (2023) - 2022
- [c51]Fan Wu, Linyi Li, Huan Zhang, Bhavya Kailkhura, Krishnaram Kenthapadi, Ding Zhao, Bo Li:
COPA: Certifying Robust Policies for Offline Reinforcement Learning against Poisoning Attacks. ICLR 2022 - [c50]Tianlong Chen, Huan Zhang, Zhenyu Zhang, Shiyu Chang, Sijia Liu, Pin-Yu Chen, Zhangyang Wang:
Linearity Grafting: Relaxed Neuron Pruning Helps Certifiable Robustness. ICML 2022: 3760-3772 - [c49]Huan Zhang, Shiqi Wang, Kaidi Xu, Yihan Wang, Suman Jana, Cho-Jui Hsieh, J. Zico Kolter:
A Branch and Bound Framework for Stronger Adversarial Attacks of ReLU Networks. ICML 2022: 26591-26604 - [c48]Jun-Ho Choi, Huan Zhang, Jun-Hyuk Kim, Cho-Jui Hsieh, Jong-Seok Lee:
Deep Image Destruction: Vulnerability of Deep Image-to-Image Models against Adversarial Attacks. ICPR 2022: 1287-1293 - [c47]Li-Cheng Lan, Huan Zhang, Ti-Rong Wu, Meng-Yu Tsai, I-Chen Wu, Cho-Jui Hsieh:
Are AlphaZero-like Agents Robust to Adversarial Perturbations? NeurIPS 2022 - [c46]Zhouxing Shi, Yihan Wang, Huan Zhang, J. Zico Kolter, Cho-Jui Hsieh:
Efficiently Computing Local Lipschitz Constants of Neural Networks via Bound Propagation. NeurIPS 2022 - [c45]Huan Zhang, Shiqi Wang, Kaidi Xu, Linyi Li, Bo Li, Suman Jana, Cho-Jui Hsieh, J. Zico Kolter:
General Cutting Planes for Bound-Propagation-Based Neural Network Verification. NeurIPS 2022 - [i48]Fan Wu, Linyi Li, Chejian Xu, Huan Zhang, Bhavya Kailkhura, Krishnaram Kenthapadi, Ding Zhao, Bo Li:
COPA: Certifying Robust Policies for Offline Reinforcement Learning against Poisoning Attacks. CoRR abs/2203.08398 (2022) - [i47]Tianlong Chen, Huan Zhang, Zhenyu Zhang, Shiyu Chang, Sijia Liu, Pin-Yu Chen, Zhangyang Wang:
Linearity Grafting: Relaxed Neuron Pruning Helps Certifiable Robustness. CoRR abs/2206.07839 (2022) - [i46]Huan Zhang, Shiqi Wang, Kaidi Xu, Linyi Li, Bo Li, Suman Jana, Cho-Jui Hsieh, J. Zico Kolter:
General Cutting Planes for Bound-Propagation-Based Neural Network Verification. CoRR abs/2208.05740 (2022) - [i45]Zhouxing Shi, Yihan Wang, Huan Zhang, J. Zico Kolter, Cho-Jui Hsieh:
Efficiently Computing Local Lipschitz Constants of Neural Networks via Bound Propagation. CoRR abs/2210.07394 (2022) - [i44]Yujia Huang, Ivan Dario Jimenez Rodriguez, Huan Zhang, Yuanyuan Shi, Yisong Yue:
FI-ODE: Certified and Robust Forward Invariance in Neural ODEs. CoRR abs/2210.16940 (2022) - [i43]Li-Cheng Lan, Huan Zhang, Ti-Rong Wu, Meng-Yu Tsai, I-Chen Wu, Cho-Jui Hsieh:
Are AlphaZero-like Agents Robust to Adversarial Perturbations? CoRR abs/2211.03769 (2022) - 2021
- [c44]Kaidi Xu, Huan Zhang, Shiqi Wang, Yihan Wang, Suman Jana, Xue Lin, Cho-Jui Hsieh:
Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers. ICLR 2021 - [c43]Huan Zhang, Hongge Chen, Duane S. Boning, Cho-Jui Hsieh:
Robust Reinforcement Learning on State Observations with Learned Optimal Adversary. ICLR 2021 - [c42]Chong Zhang, Jieyu Zhao, Huan Zhang, Kai-Wei Chang, Cho-Jui Hsieh:
Double Perturbation: On the Robustness of Robustness and Counterfactual Bias Evaluation. NAACL-HLT 2021: 3899-3916 - [c41]Zhouxing Shi, Yihan Wang, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh:
Fast Certified Robust Training with Short Warmup. NeurIPS 2021: 18335-18349 - [c40]Yujia Huang, Huan Zhang, Yuanyuan Shi, J. Zico Kolter, Anima Anandkumar:
Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds. NeurIPS 2021: 22745-22757 - [c39]Leslie Rice, Anna Bair, Huan Zhang, J. Zico Kolter:
Robustness between the worst and average case. NeurIPS 2021: 27840-27851 - [c38]Shiqi Wang, Huan Zhang, Kaidi Xu, Xue Lin, Suman Jana, Cho-Jui Hsieh, J. Zico Kolter:
Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Neural Network Robustness Verification. NeurIPS 2021: 29909-29921 - [i42]Huan Zhang, Hongge Chen, Duane S. Boning, Cho-Jui Hsieh:
Robust Reinforcement Learning on State Observations with Learned Optimal Adversary. CoRR abs/2101.08452 (2021) - [i41]Shiqi Wang, Huan Zhang, Kaidi Xu, Xue Lin, Suman Jana, Cho-Jui Hsieh, J. Zico Kolter:
Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Complete and Incomplete Neural Network Verification. CoRR abs/2103.06624 (2021) - [i40]Zhouxing Shi, Yihan Wang, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh:
Fast Certified Robust Training via Better Initialization and Shorter Warmup. CoRR abs/2103.17268 (2021) - [i39]Chong Zhang, Jieyu Zhao, Huan Zhang, Kai-Wei Chang, Cho-Jui Hsieh:
Double Perturbation: On the Robustness of Robustness and Counterfactual Bias Evaluation. CoRR abs/2104.05232 (2021) - [i38]Jun-Ho Choi, Huan Zhang, Jun-Hyuk Kim, Cho-Jui Hsieh, Jong-Seok Lee:
Deep Image Destruction: A Comprehensive Study on Vulnerability of Deep Image-to-Image Models against Adversarial Attacks. CoRR abs/2104.15022 (2021) - [i37]Alexander Pan, Yongkyun Lee, Huan Zhang, Yize Chen, Yuanyuan Shi:
Improving Robustness of Reinforcement Learning for Power System Control with Adversarial Training. CoRR abs/2110.08956 (2021) - [i36]Yujia Huang, Huan Zhang, Yuanyuan Shi, J. Zico Kolter, Anima Anandkumar:
Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds. CoRR abs/2111.01395 (2021) - [i35]Jaehui Hwang, Huan Zhang, Jun-Ho Choi, Cho-Jui Hsieh, Jong-Seok Lee:
Temporal Shuffling for Defending Deep Action Recognition Models against Adversarial Attacks. CoRR abs/2112.07921 (2021) - 2020
- [b1]Huan Zhang:
Machine Learning with Provable Robustness Guarantees. University of California, Los Angeles, USA, 2020 - [j1]Lu Wang, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, Yuan Jiang:
Spanning attack: reinforce black-box attacks with unlabeled data. Mach. Learn. 109(12): 2349-2368 (2020) - [c37]Minhao Cheng, Jinfeng Yi, Pin-Yu Chen, Huan Zhang, Cho-Jui Hsieh:
Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples. AAAI 2020: 3601-3608 - [c36]Jun-Ho Choi, Huan Zhang, Jun-Hyuk Kim, Cho-Jui Hsieh, Jong-Seok Lee:
Adversarially Robust Deep Image Super-Resolution Using Entropy Regularization. ACCV (4) 2020: 301-317 - [c35]Zhouxing Shi, Huan Zhang, Kai-Wei Chang, Minlie Huang, Cho-Jui Hsieh:
Robustness Verification for Transformers. ICLR 2020 - [c34]Runtian Zhai, Chen Dan, Di He, Huan Zhang, Boqing Gong, Pradeep Ravikumar, Cho-Jui Hsieh, Liwei Wang:
MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius. ICLR 2020 - [c33]Huan Zhang, Hongge Chen, Chaowei Xiao, Sven Gowal, Robert Stanforth, Bo Li, Duane S. Boning, Cho-Jui Hsieh:
Towards Stable and Efficient Training of Verifiably Robust Neural Networks. ICLR 2020 - [c32]Yihan Wang, Huan Zhang, Hongge Chen, Duane S. Boning, Cho-Jui Hsieh:
On Lp-norm Robustness of Ensemble Decision Stumps and Trees. ICML 2020: 10104-10114 - [c31]Huan Zhang, Hongge Chen, Chaowei Xiao, Bo Li, Mingyan Liu, Duane S. Boning, Cho-Jui Hsieh:
Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations. NeurIPS 2020 - [c30]Kaidi Xu, Zhouxing Shi, Huan Zhang, Yihan Wang, Kai-Wei Chang, Minlie Huang, Bhavya Kailkhura, Xue Lin, Cho-Jui Hsieh:
Automatic Perturbation Analysis for Scalable Certified Robustness and Beyond. NeurIPS 2020 - [c29]Chong Zhang, Huan Zhang, Cho-Jui Hsieh:
An Efficient Adversarial Attack for Tree Ensembles. NeurIPS 2020 - [i34]Runtian Zhai, Chen Dan, Di He, Huan Zhang, Boqing Gong, Pradeep Ravikumar, Cho-Jui Hsieh, Liwei Wang:
MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius. CoRR abs/2001.02378 (2020) - [i33]Zhouxing Shi, Huan Zhang, Kai-Wei Chang, Minlie Huang, Cho-Jui Hsieh:
Robustness Verification for Transformers. CoRR abs/2002.06622 (2020) - [i32]Kaidi Xu, Zhouxing Shi, Huan Zhang, Minlie Huang, Kai-Wei Chang, Bhavya Kailkhura, Xue Lin, Cho-Jui Hsieh:
Automatic Perturbation Analysis on General Computational Graphs. CoRR abs/2002.12920 (2020) - [i31]Huan Zhang, Hongge Chen, Chaowei Xiao, Bo Li, Duane S. Boning, Cho-Jui Hsieh:
Robust Deep Reinforcement Learning against Adversarial Perturbations on Observations. CoRR abs/2003.08938 (2020) - [i30]Lu Wang, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, Yuan Jiang:
Spanning Attack: Reinforce Black-box Attacks with Unlabeled Data. CoRR abs/2005.04871 (2020) - [i29]Yang You, Yuhui Wang, Huan Zhang, Zhao Zhang, James Demmel, Cho-Jui Hsieh:
The Limit of the Batch Size. CoRR abs/2006.08517 (2020) - [i28]Yihan Wang, Huan Zhang, Hongge Chen, Duane S. Boning, Cho-Jui Hsieh:
On 𝓁p-norm Robustness of Ensemble Stumps and Trees. CoRR abs/2008.08755 (2020) - [i27]Chong Zhang, Huan Zhang, Cho-Jui Hsieh:
An Efficient Adversarial Attack for Tree Ensembles. CoRR abs/2010.11598 (2020) - [i26]Kaidi Xu, Huan Zhang, Shiqi Wang, Yihan Wang, Suman Jana, Xue Lin, Cho-Jui Hsieh:
Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers. CoRR abs/2011.13824 (2020)
2010 – 2019
- 2019
- [c28]Chun-Chen Tu, Pai-Shun Ting, Pin-Yu Chen, Sijia Liu, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, Shin-Ming Cheng:
AutoZOOM: Autoencoder-Based Zeroth Order Optimization Method for Attacking Black-Box Neural Networks. AAAI 2019: 742-749 - [c27]Huan Zhang, Pengchuan Zhang, Cho-Jui Hsieh:
RecurJac: An Efficient Recursive Algorithm for Bounding Jacobian Matrix of Neural Networks and Its Applications. AAAI 2019: 5757-5764 - [c26]Yifan Ding, Liqiang Wang, Huan Zhang, Jinfeng Yi, Deliang Fan, Boqing Gong:
Defending Against Adversarial Attacks Using Random Forest. CVPR Workshops 2019: 105-114 - [c25]Moustafa Alzantot, Yash Sharma, Supriyo Chakraborty, Huan Zhang, Cho-Jui Hsieh, Mani B. Srivastava:
GenAttack: practical black-box attacks with gradient-free optimization. GECCO 2019: 1111-1119 - [c24]Shaokai Ye, Xue Lin, Kaidi Xu, Sijia Liu, Hao Cheng, Jan-Henrik Lambrechts, Huan Zhang, Aojun Zhou, Kaisheng Ma, Yanzhi Wang:
Adversarial Robustness vs. Model Compression, or Both? ICCV 2019: 111-120 - [c23]Jun-Ho Choi, Huan Zhang, Jun-Hyuk Kim, Cho-Jui Hsieh, Jong-Seok Lee:
Evaluating Robustness of Deep Image Super-Resolution Against Adversarial Attacks. ICCV 2019: 303-311 - [c22]Minhao Cheng, Thong Le, Pin-Yu Chen, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh:
Query-Efficient Hard-label Black-box Attack: An Optimization-based Approach. ICLR (Poster) 2019 - [c21]Kaidi Xu, Sijia Liu, Pu Zhao, Pin-Yu Chen, Huan Zhang, Quanfu Fan, Deniz Erdogmus, Yanzhi Wang, Xue Lin:
Structured Adversarial Attack: Towards General Implementation and Better Interpretability. ICLR (Poster) 2019 - [c20]Huan Zhang, Hongge Chen, Zhao Song, Duane S. Boning, Inderjit S. Dhillon, Cho-Jui Hsieh:
The Limitations of Adversarial Training and the Blind-Spot Attack. ICLR (Poster) 2019 - [c19]Hongge Chen, Huan Zhang, Duane S. Boning, Cho-Jui Hsieh:
Robust Decision Trees Against Adversarial Examples. ICML 2019: 1122-1131 - [c18]Hadi Salman, Greg Yang, Huan Zhang, Cho-Jui Hsieh, Pengchuan Zhang:
A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks. NeurIPS 2019: 9832-9842 - [c17]Hongge Chen, Huan Zhang, Si Si, Yang Li, Duane S. Boning, Cho-Jui Hsieh:
Robustness Verification of Tree-based Models. NeurIPS 2019: 12317-12328 - [i25]Huan Zhang, Hongge Chen, Zhao Song, Duane S. Boning, Inderjit S. Dhillon, Cho-Jui Hsieh:
The Limitations of Adversarial Training and the Blind-Spot Attack. CoRR abs/1901.04684 (2019) - [i24]Hadi Salman, Greg Yang, Huan Zhang, Cho-Jui Hsieh, Pengchuan Zhang:
A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks. CoRR abs/1902.08722 (2019) - [i23]Hongge Chen, Huan Zhang, Duane S. Boning, Cho-Jui Hsieh:
Robust Decision Trees Against Adversarial Examples. CoRR abs/1902.10660 (2019) - [i22]Shaokai Ye, Kaidi Xu, Sijia Liu, Hao Cheng, Jan-Henrik Lambrechts, Huan Zhang, Aojun Zhou, Kaisheng Ma, Yanzhi Wang, Xue Lin:
Second Rethinking of Network Pruning in the Adversarial Setting. CoRR abs/1903.12561 (2019) - [i21]Jun-Ho Choi, Huan Zhang, Jun-Hyuk Kim, Cho-Jui Hsieh, Jong-Seok Lee:
Evaluating Robustness of Deep Image Super-Resolution against Adversarial Attacks. CoRR abs/1904.06097 (2019) - [i20]Hongge Chen, Huan Zhang, Si Si, Yang Li, Duane S. Boning, Cho-Jui Hsieh:
Robustness Verification of Tree-based Models. CoRR abs/1906.03849 (2019) - [i19]Huan Zhang, Hongge Chen, Chaowei Xiao, Bo Li, Duane S. Boning, Cho-Jui Hsieh:
Towards Stable and Efficient Training of Verifiably Robust Neural Networks. CoRR abs/1906.06316 (2019) - [i18]Yifan Ding, Liqiang Wang, Huan Zhang, Jinfeng Yi, Deliang Fan, Boqing Gong:
Defending Against Adversarial Attacks Using Random Forests. CoRR abs/1906.06765 (2019) - [i17]Huan Zhang, Minhao Cheng, Cho-Jui Hsieh:
Enhancing Certifiable Robustness via a Deep Model Ensemble. CoRR abs/1910.14655 (2019) - 2018
- [c16]Pin-Yu Chen, Yash Sharma, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh:
EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples. AAAI 2018: 10-17 - [c15]Hongge Chen, Huan Zhang, Pin-Yu Chen, Jinfeng Yi, Cho-Jui Hsieh:
Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning. ACL (1) 2018: 2587-2597 - [c14]Xuanqing Liu, Minhao Cheng, Huan Zhang, Cho-Jui Hsieh:
Towards Robust Neural Networks via Random Self-ensemble. ECCV (7) 2018: 381-397 - [c13]Dong Su, Huan Zhang, Hongge Chen, Jinfeng Yi, Pin-Yu Chen, Yupeng Gao:
Is Robustness the Cost of Accuracy? - A Comprehensive Study on the Robustness of 18 Deep Image Classification Models. ECCV (12) 2018: 644-661 - [c12]Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen, Aurélie C. Lozano, Cho-Jui Hsieh, Luca Daniel:
On Extensions of Clever: A Neural Network Robustness Evaluation Algorithm. GlobalSIP 2018: 1159-1163 - [c11]Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen, Jinfeng Yi, Dong Su, Yupeng Gao, Cho-Jui Hsieh, Luca Daniel:
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach. ICLR (Poster) 2018 - [c10]Tsui-Wei Weng, Huan Zhang, Hongge Chen, Zhao Song, Cho-Jui Hsieh, Luca Daniel, Duane S. Boning, Inderjit S. Dhillon:
Towards Fast Computation of Certified Robustness for ReLU Networks. ICML 2018: 5273-5282 - [c9]Huan Zhang, Tsui-Wei Weng, Pin-Yu Chen, Cho-Jui Hsieh, Luca Daniel:
Efficient Neural Network Robustness Certification with General Activation Functions. NeurIPS 2018: 4944-4953 - [c8]Po-Wei Wang, Huan Zhang, Vijai Mohan, Inderjit S. Dhillon, J. Zico Kolter:
Realtime Query Completion via Deep Language Models. eCOM@SIGIR 2018 - [i16]Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen, Jinfeng Yi, Dong Su, Yupeng Gao, Cho-Jui Hsieh, Luca Daniel:
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach. CoRR abs/1801.10578 (2018) - [i15]Minhao Cheng, Jinfeng Yi, Huan Zhang, Pin-Yu Chen, Cho-Jui Hsieh:
Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples. CoRR abs/1803.01128 (2018) - [i14]Tsui-Wei Weng, Huan Zhang, Hongge Chen, Zhao Song, Cho-Jui Hsieh, Duane S. Boning, Inderjit S. Dhillon, Luca Daniel:
Towards Fast Computation of Certified Robustness for ReLU Networks. CoRR abs/1804.09699 (2018) - [i13]Chun-Chen Tu, Pai-Shun Ting, Pin-Yu Chen, Sijia Liu, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, Shin-Ming Cheng:
AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks. CoRR abs/1805.11770 (2018) - [i12]Minhao Cheng, Thong Le, Pin-Yu Chen, Jinfeng Yi, Huan Zhang, Cho-Jui Hsieh:
Query-Efficient Hard-label Black-box Attack: An Optimization-based Approach. CoRR abs/1807.04457 (2018) - [i11]Kaidi Xu, Sijia Liu, Pu Zhao, Pin-Yu Chen, Huan Zhang, Deniz Erdogmus, Yanzhi Wang, Xue Lin:
Structured Adversarial Attack: Towards General Implementation and Better Interpretability. CoRR abs/1808.01664 (2018) - [i10]Dong Su, Huan Zhang, Hongge Chen, Jinfeng Yi, Pin-Yu Chen, Yupeng Gao:
Is Robustness the Cost of Accuracy? - A Comprehensive Study on the Robustness of 18 Deep Image Classification Models. CoRR abs/1808.01688 (2018) - [i9]Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen, Aurélie C. Lozano, Cho-Jui Hsieh, Luca Daniel:
On Extensions of CLEVER: A Neural Network Robustness Evaluation Algorithm. CoRR abs/1810.08640 (2018) - [i8]Huan Zhang, Pengchuan Zhang, Cho-Jui Hsieh:
RecurJac: An Efficient Recursive Algorithm for Bounding Jacobian Matrix of Neural Networks and Its Applications. CoRR abs/1810.11783 (2018) - [i7]Huan Zhang, Tsui-Wei Weng, Pin-Yu Chen, Cho-Jui Hsieh, Luca Daniel:
Efficient Neural Network Robustness Certification with General Activation Functions. CoRR abs/1811.00866 (2018) - 2017
- [c7]Pin-Yu Chen, Huan Zhang, Yash Sharma, Jinfeng Yi, Cho-Jui Hsieh:
ZOO: Zeroth Order Optimization Based Black-box Attacks to Deep Neural Networks without Training Substitute Models. AISec@CCS 2017: 15-26 - [c6]Si Si, Huan Zhang, S. Sathiya Keerthi, Dhruv Mahajan, Inderjit S. Dhillon, Cho-Jui Hsieh:
Gradient Boosted Decision Trees for High Dimensional Sparse Output. ICML 2017: 3182-3190 - [c5]Xiangru Lian, Ce Zhang, Huan Zhang, Cho-Jui Hsieh, Wei Zhang, Ji Liu:
Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent. NIPS 2017: 5330-5340 - [i6]Xiangru Lian, Ce Zhang, Huan Zhang, Cho-Jui Hsieh, Wei Zhang, Ji Liu:
Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent. CoRR abs/1705.09056 (2017) - [i5]Huan Zhang, Si Si, Cho-Jui Hsieh:
GPU-acceleration for Large-scale Tree Boosting. CoRR abs/1706.08359 (2017) - [i4]Pin-Yu Chen, Huan Zhang, Yash Sharma, Jinfeng Yi, Cho-Jui Hsieh:
ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute Models. CoRR abs/1708.03999 (2017) - [i3]Pin-Yu Chen, Yash Sharma, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh:
EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples. CoRR abs/1709.04114 (2017) - [i2]Xuanqing Liu, Minhao Cheng, Huan Zhang, Cho-Jui Hsieh:
Towards Robust Neural Networks via Random Self-ensemble. CoRR abs/1712.00673 (2017) - [i1]Hongge Chen, Huan Zhang, Pin-Yu Chen, Jinfeng Yi, Cho-Jui Hsieh:
Show-and-Fool: Crafting Adversarial Examples for Neural Image Captioning. CoRR abs/1712.02051 (2017) - 2016
- [c4]Huan Zhang, Cho-Jui Hsieh:
Fixing the Convergence Problems in Parallel Asynchronous Dual Coordinate Descent. ICDM 2016: 619-628 - [c3]Huan Zhang, Cho-Jui Hsieh, Venkatesh Akella:
HogWild++: A New Mechanism for Decentralized Asynchronous Stochastic Gradient Descent. ICDM 2016: 629-638 - [c2]Zhao Song, David P. Woodruff, Huan Zhang:
Sublinear Time Orthogonal Tensor Decomposition. NIPS 2016: 793-801 - [c1]Xiangru Lian, Huan Zhang, Cho-Jui Hsieh, Yijun Huang, Ji Liu:
A Comprehensive Linear Speedup Analysis for Asynchronous Stochastic Parallel Optimization from Zeroth-Order to First-Order. NIPS 2016: 3054-3062
Coauthor Index
[j2] [i52] [c53] [i50] [c49] [c48] [c47] [c46] [c45] [i46] [i45] [i43] [c44] [c43] [c42] [c41] [c38] [i42] [i41] [i40] [i39] [i38] [i35] [j1] [c37] [c36] [c35] [c34] [c33] [c32] [c31] [c30] [c29] [i34] [i33] [i32] [i31] [i30] [i29] [i28] [i27] [i26] [c28] [c27] [c25] [c23] [c22] [c20] [c19] [c18] [c17] [i25] [i24] [i23] [i21] [i20] [i19] [i17] [c16] [c15] [c14] [c12] [c11] [c10] [c9] [i16] [i15] [i14] [i13] [i12] [i9] [i8] [i7] [c7] [c6] [c5] [i6] [i5] [i4] [i3] [i2] [i1] [c4] [c3] [c1]
J. Zico Kolter
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aka: Zico Kolter
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