Are Adversarial Examples Created Equal? A Learnable Weighted Minimax Risk for Robustness under Non-Uniform Attacks
35th AAAI Conference on Artificial Intelligence (AAAI), 2021.
Huimin Zeng, Chen Zhu, Tom Goldstein and Furong Huang
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Certifiably Robust Multi-Agent Reinforcement Learning against Adversarial Communication
accepted to the Responsible Decision Making in Dynamic Environments Workshop @ICML2022.
Yanchao Sun, Ruijie Zheng, Parisa Hassanzadeh, Yongyuan Liang, Soheil Feizi, Sumitra Ganesh, Furong Huang
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Efficient Adversarial Training without Attacking: Worst-Case-Aware Robust Reinforcement Learning
accepted to the Responsible Decision Making in Dynamic Environments Workshop @ICML2022.
Yongyuan Liang, Yanchao Sun, Ruijie Zheng, Furong Huang
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Everyone Matters: Customizing the Dynamics of Decision Boundary for Adversarial Robustness
accepted at the ICML workshop for Continuous Time Methods for Machine Learning @ICML2022.
Yuancheng Xu, Yanchao Sun, Furong Huang
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Live in the Moment: Learning Dynamics Model Adapted to Evolving Policy
accepted for a spotlight presentation workshop of Decision Awareness
in Reinforcement Learning (DARL) @ICML2022.
Xiyao Wang, Wichayaporn Wongkamjan, Furong Huang
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Transfer Fairness under Distribution Shifts
ICLR Workshop on Socially Responsible Machine Learning, @ICLR 2022.
Bang An, Zora Che, Mucong Ding, Furong Huang
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Practical and Fast Momentum-Based Power Methods
2nd Annual Conference on Mathematical and Scientific Machine Learning, Proceedings of Machine Learning Research vol 145:1-36, 2021.
Tahseen Rabbani, Apollo Jain, Arjun Rajkumar, Furong Huang
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Understanding Generalization in Deep Learning via Tensor Methods
Twenty-third International Conference on Artificial Intelligence and Statistics (AISTATS), 2020.
J. Li, Y. Sun, J. Su, T. Suzuki, F. Huang
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ARMA Nets: Expanding Receptive Field for Dense Prediction
Neural Information Processing System (NeurIPS), 2020
Jiahao Su, Shiqi Wang, Furong Huang
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MaxVA: Fast Adaptation of Stepsizes by Maximizing Observed Variance of Gradients
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2021.
Chen Zhu, Yu Cheng, Zhe Gan, Furong Huang, Jingjing Liu, Tom Goldstein
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