| Openai o1 system card A Jaech, A Kalai, A Lerer, A Richardson, A El-Kishky, A Low, A Helyar, ... arXiv preprint arXiv:2412.16720, 2024 | 1518 | 2024 |
| High-dimensional sparse linear bandits B Hao, T Lattimore, M Wang 34th Conference on Neural Information Processing Systems, 2020 | 99 | 2020 |
| Simultaneous clustering and estimation of heterogeneous graphical models B Hao, WW Sun, Y Liu, G Cheng Journal of Machine Learning Research 18 (217), 1-58, 2018 | 95 | 2018 |
| Adaptive exploration in linear contextual bandit B Hao, T Lattimore, C Szepesvari International Conference on Artificial Intelligence and Statistics, 3536-3545, 2020 | 88 | 2020 |
| Bootstrapping upper confidence bound B Hao, Y Abbasi-Yadkori, Z Wen, G Cheng 33rd Conference on Neural Information Processing Systems, 2019 | 79 | 2019 |
| Sparse and low-rank tensor estimation via cubic sketchings B Hao, AR Zhang, G Cheng International conference on artificial intelligence and statistics, 1319-1330, 2020 | 68 | 2020 |
| Bootstrapping fitted q-evaluation for off-policy inference B Hao, X Ji, Y Duan, H Lu, C Szepesvari, M Wang International Conference on Machine Learning, 4074-4084, 2021 | 60 | 2021 |
| Efficient exploration for llms V Dwaracherla, SM Asghari, B Hao, B Van Roy arXiv preprint arXiv:2402.00396, 2024 | 47 | 2024 |
| Online sparse reinforcement learning B Hao, T Lattimore, C Szepesvári, M Wang International Conference on Artificial Intelligence and Statistics, 316-324, 2021 | 44 | 2021 |
| Sparse feature selection makes batch reinforcement learning more sample efficient B Hao, Y Duan, T Lattimore, C Szepesvári, M Wang International Conference on Machine Learning, 4063-4073, 2021 | 41 | 2021 |
| Efficient local planning with linear function approximation D Yin, B Hao, Y Abbasi-Yadkori, N Lazić, C Szepesvári International Conference on Algorithmic Learning Theory, 1165-1192, 2022 | 39 | 2022 |
| Sparse tensor additive regression B Hao, B Wang, P Wang, J Zhang, J Yang, WW Sun Journal of machine learning research 22 (64), 1-43, 2021 | 37 | 2021 |
| Adaptive approximate policy iteration B Hao, N Lazic, Y Abbasi-Yadkori, P Joulani, C Szepesvari Proceedings of the 24th International Conference on Artificial Intelligence …, 2020 | 31* | 2020 |
| The neural testbed: Evaluating joint predictions I Osband, Z Wen, SM Asghari, V Dwaracherla, X Lu, M Ibrahimi, ... Advances in Neural Information Processing Systems 35, 12554-12565, 2022 | 30 | 2022 |
| Regret Bounds for Information-Directed Reinforcement Learning B Hao, T Lattimore Advances in Neural Information Processing Systems, 2022 | 27 | 2022 |
| Information directed sampling for sparse linear bandits B Hao, T Lattimore, W Deng Advances in Neural Information Processing Systems 34, 16738-16750, 2021 | 24 | 2021 |
| Contextual information-directed sampling B Hao, T Lattimore, C Qin International Conference on Machine Learning, 8446-8464, 2022 | 23 | 2022 |
| Residual bootstrap exploration for bandit algorithms CH Wang, Y Yu, B Hao, G Cheng arXiv preprint arXiv:2002.08436, 2020 | 22 | 2020 |
| Leveraging demonstrations to improve online learning: Quality matters B Hao, R Jain, T Lattimore, B Van Roy, Z Wen International Conference on Machine Learning, 12527-12545, 2023 | 18 | 2023 |
| Tensors in modern statistical learning WW Sun, B Hao, L Li Wiley StatsRef: Statistics Reference Online, 1-25, 2021 | 18 | 2021 |
Tor LattimoreGoogle DeepMindVerified email at google.com
