| Simultaneous clustering and estimation of heterogeneous graphical models B Hao, WW Sun, Y Liu, G Cheng Journal of Machine Learning Research, 2018 | 59 | 2018 |
| 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 | 50 | 2020 |
| Adaptive exploration in linear contextual bandit B Hao, T Lattimore, C Szepesvari International Conference on Artificial Intelligence and Statistics, 3536-3545, 2020 | 45 | 2020 |
| Bootstrapping upper confidence bound B Hao, Y Abbasi-Yadkori, Z Wen, G Cheng 33rd Conference on Neural Information Processing Systems, 2019 | 43 | 2019 |
| High-dimensional sparse linear bandits B Hao, T Lattimore, M Wang 34th Conference on Neural Information Processing Systems, 2020 | 35 | 2020 |
| 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 | 26 | 2021 |
| Online sparse reinforcement learning B Hao, T Lattimore, C Szepesvári, M Wang International Conference on Artificial Intelligence and Statistics, 316-324, 2021 | 24 | 2021 |
| Sparse tensor additive regression B Hao, B Wang, P Wang, J Zhang, J Yang, WW Sun The Journal of Machine Learning Research 22 (1), 2989-3031, 2021 | 22 | 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 | 21* | 2020 |
| Bootstrapping fitted q-evaluation for off-policy inference B Hao, X Ji, Y Duan, H Lu, C Szepesvári, M Wang International Conference on Machine Learning, 4074-4084, 2021 | 16 | 2021 |
| Bootstrapping Statistical Inference for Off-Policy Evaluation B Hao, X Ji, Y Duan, H Lu, C Szepesvári, M Wang arXiv preprint arXiv:2102.03607, 2021 | 15 | 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 | 14 | 2022 |
| Information directed sampling for sparse linear bandits B Hao, T Lattimore, W Deng Advances in Neural Information Processing Systems 34, 16738-16750, 2021 | 13 | 2021 |
| Residual bootstrap exploration for bandit algorithms CH Wang, Y Yu, B Hao, G Cheng arXiv preprint arXiv:2002.08436, 2020 | 12 | 2020 |
| Optimization issues in kl-constrained approximate policy iteration N Lazić, B Hao, Y Abbasi-Yadkori, D Schuurmans, C Szepesvári arXiv preprint arXiv:2102.06234, 2021 | 11 | 2021 |
| Bandit phase retrieval T Lattimore, B Hao Advances in Neural Information Processing Systems 34, 18801-18811, 2021 | 8 | 2021 |
| Nonparametric Bayesian Aggregation for Massive Data. Z Shang, B Hao, G Cheng J. Mach. Learn. Res. 20, 140:1-140:81, 2019 | 8 | 2019 |
| Low-rank tensor bandits B Hao, J Zhou, Z Wen, WW Sun arXiv preprint arXiv:2007.15788, 2020 | 7 | 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 | 6 | 2022 |
| Regret Bounds for Information-Directed Reinforcement Learning B Hao, T Lattimore Advances in Neural Information Processing Systems, 2022 | 6 | 2022 |
Csaba SzepesvariDeepMind & University of AlbertaAdresse e-mail validée de cs.ualberta.ca
