My Google Scholar page is here with the full list of papers including pre-prints
Publications
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Robust Multi-Agent Reinforcement Learning via Minimax Deep Deterministic Policy Gradient (AAAI 2019)
Shihui Li, Yi Wu, Xinyue Cui, Honghua Dong, Fei Fang, Stuart Russell |
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Deep Reinforcement Learning for Green Security Games with Real-Time Information (AAAI 2019)
Yufei Wang, Zheyuan Ryan Shi, Lantao Yu, Yi Wu, Rohit Singh, Lucas Joppa, Fei Fang |
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Discrete-Continuous Mixtures in Probabilistic Programming: Generalized Semantics and Inference Algorithms (ICML 2018)
Yi Wu, Siddharth Srivastava, Nicholas Hay, Simon S. Du, Stuart Russell A short version was accepted in PPS workshop, POPL 2017 |
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Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments (NIPS 2017)
Ryan Lowe*, Yi Wu*, Aviv Tamar, Jean Harb, Pieter Abbeel, Igor Mordatch (* equal contribution) The OpenAI blog for this work is here |
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Adversarial Training for Relation Extraction (EMNLP 2017)
Yi Wu, David Bamman, Stuart Russell Source code can be found here |
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A Nearly-Black-Box Online Algorithm for Joint Parameter and State Estimation in Temporal Models (AAAI 2017, Oral)
Yusuf B. Erol*, Yi Wu*, Lei Li, Stuart Russell (* equal contribution) Supplementary materials are here |
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Value Iteration Network (NIPS 2016, Best Paper Award)
Aviv Tamar, Yi Wu, Garrett Thomas, Sergey Levine, Pieter Abbeel |
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Understanding and Evaluating Sparse Linear Discriminant Analysis (AISTATS 2015, Oral)
Yi Wu, David Wipf, Jeong-Min Yun |
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Dual Space Analysis of the Sparse Linear Model (NIPS2012)
David Wipf, Yi Wu |
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Workshop Papers
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Building Generalizable Agents with a Realistic and Rich 3D Environment
(NIPS2017 Deep Reinforcement Learning Symposium; ICLR 2018 Workshop Track) Check the Github page of our House3D project |
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BFiT: From Possible-World Semantics to Random-Evaluation Semantics in an Open Universe
(NIPS 2014 workshop on Probabilistic Programming, spotlight) |
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