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Young Wu
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2020 – today
- 2024
- [c5]Jeremy McMahan, Young Wu, Xiaojin Zhu, Qiaomin Xie:
Optimal Attack and Defense for Reinforcement Learning. AAAI 2024: 14332-14340 - [c4]Young Wu, Jeremy McMahan, Xiaojin Zhu, Qiaomin Xie:
Data Poisoning to Fake a Nash Equilibria for Markov Games. AAAI 2024: 15979-15987 - [c3]Young Wu, Jeremy McMahan, Yiding Chen, Yudong Chen, Jerry Zhu, Qiaomin Xie:
Minimally Modifying a Markov Game to Achieve Any Nash Equilibrium and Value. ICML 2024 - [i7]Jeremy McMahan, Young Wu, Yudong Chen, Xiaojin Zhu, Qiaomin Xie:
Inception: Efficiently Computable Misinformation Attacks on Markov Games. CoRR abs/2406.17114 (2024) - 2023
- [c2]Young Wu, Jeremy McMahan, Xiaojin Zhu, Qiaomin Xie:
Reward Poisoning Attacks on Offline Multi-Agent Reinforcement Learning. AAAI 2023: 10426-10434 - [i6]Young Wu, Jeremy McMahan, Xiaojin Zhu, Qiaomin Xie:
On Faking a Nash Equilibrium. CoRR abs/2306.08041 (2023) - [i5]Jeremy McMahan, Young Wu, Yudong Chen, Xiaojin Zhu, Qiaomin Xie:
VISER: A Tractable Solution Concept for Games with Information Asymmetry. CoRR abs/2307.09652 (2023) - [i4]Young Wu, Jeremy McMahan, Yiding Chen, Yudong Chen, Xiaojin Zhu, Qiaomin Xie:
Minimally Modifying a Markov Game to Achieve Any Nash Equilibrium and Value. CoRR abs/2311.00582 (2023) - [i3]Jeremy McMahan, Young Wu, Xiaojin Zhu, Qiaomin Xie:
Optimal Attack and Defense for Reinforcement Learning. CoRR abs/2312.00198 (2023) - 2022
- [c1]Yuzhe Ma, Young Wu, Xiaojin Zhu:
Game Redesign in No-regret Game Playing. IJCAI 2022: 3321-3327 - [i2]Young Wu, Jeremy McMahan, Xiaojin Zhu, Qiaomin Xie:
Reward Poisoning Attacks on Offline Multi-Agent Reinforcement Learning. CoRR abs/2206.01888 (2022) - 2021
- [i1]Yuzhe Ma, Young Wu, Xiaojin Zhu:
Game Redesign in No-regret Game Playing. CoRR abs/2110.11763 (2021)
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