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cs.LG2022
Achieve Optimal Adversarial Accuracy for Adversarial Deep Learning using Stackelberg Game
Xiao-Shan Gao, Shuang Liu, Lijia Yu
Adversarial deep learning is to train robust DNNs against adversarial attacks, which is one of the major research focuses of deep learning. Game theory has been used to answer some…
cs.LG2022★ 5 cited
Improving Policy Optimization with Generalist-Specialist Learning
Zhiwei Jia, Xuanlin Li, Zhan Ling +3
Generalization in deep reinforcement learning over unseen environment variations usually requires policy learning over a large set of diverse training variations. We empirically ob…
cs.LG2022
Provably Efficient Kernelized Q-Learning
Shuang Liu, Hao Su
We propose and analyze a kernelized version of Q-learning. Although a kernel space is typically infinite-dimensional, extensive study has shown that generalization is only affected…