| Multi-agent actor-critic for mixed cooperative-competitive environments R Lowe, Y Wu, A Tamar, J Harb, P Abbeel, I Mordatch arXiv preprint arXiv:1706.02275, 2017 | 1055 | 2017 |
| Value iteration networks A Tamar, Y Wu, G Thomas, S Levine, P Abbeel arXiv preprint arXiv:1602.02867, 2016 | 417 | 2016 |
| Building generalizable agents with a realistic and rich 3d environment Y Wu, Y Wu, G Gkioxari, Y Tian arXiv preprint arXiv:1801.02209, 2018 | 168 | 2018 |
| Adversarial training for relation extraction Y Wu, D Bamman, S Russell Proceedings of the 2017 Conference on Empirical Methods in Natural Language …, 2017 | 135 | 2017 |
| 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 | 126 | 2019 |
| 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 | 56 | 2019 |
| Swift: Compiled inference for probabilistic programming languages Y Wu, L Li, S Russell, R Bodik arXiv preprint arXiv:1606.09242, 2016 | 30* | 2016 |
| 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 | 27 | 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 | 25* | 2019 |
| Meta-learning MCMC proposals T Wang, Y Wu, DA Moore, SJ Russell arXiv preprint arXiv:1708.06040, 2017 | 16 | 2017 |
| Dual-space analysis of the sparse linear model D Wipf, Y Wu arXiv preprint arXiv:1207.2422, 2012 | 16 | 2012 |
| Understanding and evaluating sparse linear discriminant analysis Y Wu, D Wipf, JM Yun Artificial Intelligence and Statistics, 1070-1078, 2015 | 15 | 2015 |
| 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 | 13 | 2018 |
| Influence-based multi-agent exploration T Wang, J Wang, Y Wu, C Zhang arXiv preprint arXiv:1910.05512, 2019 | 11 | 2019 |
| Multi-task reinforcement learning with soft modularization R Yang, H Xu, Y Wu, X Wang arXiv preprint arXiv:2003.13661, 2020 | 7 | 2020 |
| 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 | 5 | 2020 |
| A nearly-black-box online algorithm for joint parameter and state estimation in temporal models Y Erol, Y Wu, L Li, S Russell Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 3 | 2017 |
| BFiT: From possible-world semantics to random-evaluation semantics in open universe Y Wu, L Li, SJ Russell Neural Information Processing Systems, Probabilistic Programming workshop, 2014 | 2 | 2014 |
| Near-linear time local polynomial nonparametric estimation Y Wang, Y Wu, SS Du arXiv preprint arXiv:1802.09578, 2018 | 1 | 2018 |
| Unsupervised Extractive Summarization by Pre-training Hierarchical Transformers S Xu, X Zhang, Y Wu, F Wei, M Zhou arXiv preprint arXiv:2010.08242, 2020 | | 2020 |
Stuart RussellProfessor of Computer Science, University of California, BerkeleyVerified email at cs.berkeley.edu
