Yi Wu
Yi Wu
Institute for Interdisciplinary Information Sciences, Tsinghua University
Verified email at - Homepage
Cited by
Cited by
Multi-agent actor-critic for mixed cooperative-competitive environments
R Lowe, YI Wu, A Tamar, J Harb, OAI Pieter Abbeel, I Mordatch
Advances in neural information processing systems 30, 2017
Value iteration networks
A Tamar, Y Wu, G Thomas, S Levine, P Abbeel
Advances in neural information processing systems 29, 2016
Emergent tool use from multi-agent autocurricula
B Baker, I Kanitscheider, T Markov, Y Wu, G Powell, B McGrew, ...
arXiv preprint arXiv:1909.07528, 2019
Building generalizable agents with a realistic and rich 3d environment
Y Wu, Y Wu, G Gkioxari, Y Tian
arXiv preprint arXiv:1801.02209, 2018
The surprising effectiveness of ppo in cooperative multi-agent games
C Yu, A Velu, E Vinitsky, J Gao, Y Wang, A Bayen, Y Wu
Advances in Neural Information Processing Systems 35, 24611-24624, 2022
Adversarial training for relation extraction
Y Wu, D Bamman, S Russell
Proceedings of the 2017 Conference on Empirical Methods in Natural Language …, 2017
Robust multi-agent reinforcement learning via minimax deep deterministic policy gradient
S Li, Y Wu, X Cui, H Dong, F Fang, S Russell
Proceedings of the AAAI conference on artificial intelligence 33 (01), 4213-4220, 2019
Bayesian relational memory for semantic visual navigation
Y Wu, Y Wu, A Tamar, S Russell, G Gkioxari, Y Tian
Proceedings of the IEEE/CVF international conference on computer vision …, 2019
Multi-task reinforcement learning with soft modularization
R Yang, H Xu, Y Wu, X Wang
Advances in Neural Information Processing Systems 33, 4767-4777, 2020
Influence-based multi-agent exploration
T Wang, J Wang, Y Wu, C Zhang
arXiv preprint arXiv:1910.05512, 2019
Deep reinforcement learning for green security games with real-time information
Y Wang, ZR Shi, L Yu, Y Wu, R Singh, L Joppa, F Fang
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 1401-1408, 2019
Evolutionary population curriculum for scaling multi-agent reinforcement learning
Q Long, Z Zhou, A Gupta, F Fang, Y Wu, X Wang
arXiv preprint arXiv:2003.10423, 2020
Noveld: A simple yet effective exploration criterion
T Zhang, H Xu, X Wang, Y Wu, K Keutzer, JE Gonzalez, Y Tian
Advances in Neural Information Processing Systems 34, 25217-25230, 2021
Swift: Compiled inference for probabilistic programming languages
Y Wu, L Li, S Russell, R Bodik
arXiv preprint arXiv:1606.09242, 2016
Unsupervised extractive summarization by pre-training hierarchical transformers
S Xu, X Zhang, Y Wu, F Wei, M Zhou
arXiv preprint arXiv:2010.08242, 2020
Meta-learning MCMC proposals
T Wang, Y Wu, D Moore, SJ Russell
Advances in neural information processing systems 31, 2018
Discovering diverse multi-agent strategic behavior via reward randomization
Z Tang, C Yu, B Chen, H Xu, X Wang, F Fang, S Du, Y Wang, Y Wu
arXiv preprint arXiv:2103.04564, 2021
Multi-agent collaboration via reward attribution decomposition
T Zhang, H Xu, X Wang, Y Wu, K Keutzer, JE Gonzalez, Y Tian
arXiv preprint arXiv:2010.08531, 2020
Discrete-continuous mixtures in probabilistic programming: Generalized semantics and inference algorithms
Y Wu, S Srivastava, N Hay, S Du, S Russell
International Conference on Machine Learning, 5343-5352, 2018
Understanding and evaluating sparse linear discriminant analysis
Y Wu, D Wipf, JM Yun
Artificial Intelligence and Statistics, 1070-1078, 2015
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