| Degenerate feedback loops in recommender systems R Jiang, S Chiappa, T Lattimore, A György, P Kohli Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 383-390, 2019 | 258 | 2019 |
| Wasserstein fair classification R Jiang, A Pacchiano, T Stepleton, H Jiang, S Chiappa Uncertainty in artificial intelligence, 862-872, 2020 | 228 | 2020 |
| Reducing sentiment bias in language models via counterfactual evaluation PS Huang, H Zhang, R Jiang, R Stanforth, J Welbl, J Rae, V Maini, ... arXiv preprint arXiv:1911.03064, 2019 | 216 | 2019 |
| A general approach to fairness with optimal transport C Silvia, J Ray, S Tom, P Aldo, J Heinrich, A John Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3633-3640, 2020 | 87 | 2020 |
| Beyond greedy ranking: Slate optimization via list-CVAE R Jiang, S Gowal, TA Mann, DJ Rezende arXiv preprint arXiv:1803.01682, 2018 | 52 | 2018 |
| Human-level atari 200x faster S Kapturowski, V Campos, R Jiang, N Rakićević, H van Hasselt, ... arXiv preprint arXiv:2209.07550, 2022 | 45 | 2022 |
| Causally correct partial models for reinforcement learning DJ Rezende, I Danihelka, G Papamakarios, NR Ke, R Jiang, T Weber, ... arXiv preprint arXiv:2002.02836, 2020 | 36 | 2020 |
| Starcraft ii unplugged: Large scale offline reinforcement learning M Mathieu, S Ozair, S Srinivasan, C Gulcehre, S Zhang, R Jiang, ... Deep RL Workshop NeurIPS 2021, 2021 | 29 | 2021 |
| Learning from delayed outcomes via proxies with applications to recommender systems TA Mann, S Gowal, A Gyorgy, H Hu, R Jiang, B Lakshminarayanan, ... International Conference on Machine Learning, 4324-4332, 2019 | 24* | 2019 |
| Emphatic algorithms for deep reinforcement learning R Jiang, T Zahavy, Z Xu, A White, M Hessel, C Blundell, H Van Hasselt International Conference on Machine Learning, 5023-5033, 2021 | 22 | 2021 |
| Learning expected emphatic traces for deep RL R Jiang, S Zhang, V Chelu, A White, H van Hasselt Proceedings of the AAAI conference on artificial intelligence 36 (6), 7015-7023, 2022 | 16 | 2022 |
| Alphastar unplugged: Large-scale offline reinforcement learning M Mathieu, S Ozair, S Srinivasan, C Gulcehre, S Zhang, R Jiang, ... arXiv preprint arXiv:2308.03526, 2023 | 14 | 2023 |
| Learning from delayed outcomes using neural networks H Hu, R Jiang, TA Mann, SA Gowal, B Lakshminarayanan, A György US Patent 11,714,994, 2023 | 8 | 2023 |
| Degenerate Feedback Loops in Recommender Systems. AAAI R Jiang, S Chiappa, T Lattimore, A György, P Kohli ACM Conference on AI, Ethics, and Society (AIES), 2019 | 6 | 2019 |
| Scaling goal-based exploration via pruning proto-goals A Bagaria, R Jiang, R Kumar, T Schaul arXiv preprint arXiv:2302.04693, 2023 | 4 | 2023 |
| Learning from delayed outcomes using neural networks H Hu, R Jiang, TA Mann, SA Gowal, B Lakshminarayanan, A György US Patent 12,124,938, 2024 | | 2024 |
| Delayed learning, multi-objective optimization, and whole slate generation in recommender systems R Jiang Proceedings of the 3rd Workshop on Deep Learning for Recommender Systems, 2-2, 2018 | | 2018 |
