| Offline reinforcement learning with realizability and single-policy concentrability W Zhan, B Huang, A Huang, N Jiang, J Lee Conference on Learning Theory, 2730-2775, 2022 | 109 | 2022 |
| Policy mirror descent for regularized reinforcement learning: A generalized framework with linear convergence W Zhan, S Cen, B Huang, Y Chen, JD Lee, Y Chi SIAM Journal on Optimization 33 (2), 1061-1091, 2023 | 75 | 2023 |
| Fl-ntk: A neural tangent kernel-based framework for federated learning analysis B Huang, X Li, Z Song, X Yang International Conference on Machine Learning, 4423-4434, 2021 | 64 | 2021 |
| Solving sdp faster: A robust ipm framework and efficient implementation B Huang, S Jiang, Z Song, R Tao, R Zhang 2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS …, 2022 | 56 | 2022 |
| Towards general function approximation in zero-sum markov games B Huang, JD Lee, Z Wang, Z Yang arXiv preprint arXiv:2107.14702, 2021 | 55 | 2021 |
| Fl-ntk: A neural tangent kernel-based framework for federated learning convergence analysis B Huang, X Li, Z Song, X Yang arXiv preprint arXiv:2105.05001, 2021 | 19 | 2021 |
| Optimal gradient-based algorithms for non-concave bandit optimization B Huang, K Huang, S Kakade, JD Lee, Q Lei, R Wang, J Yang Advances in Neural Information Processing Systems 34, 29101-29115, 2021 | 16 | 2021 |
| Solving tall dense sdps in the current matrix multiplication time B Huang, S Jiang, Z Song, R Tao, R Zhang arXiv preprint arXiv:2101.08208 6, 1.1, 2021 | 13 | 2021 |
| A faster quantum algorithm for semidefinite programming via robust IPM framework B Huang, S Jiang, Z Song, R Tao, R Zhang arXiv preprint arXiv:2207.11154, 2022 | 9 | 2022 |
| Going beyond linear rl: Sample efficient neural function approximation B Huang, K Huang, S Kakade, JD Lee, Q Lei, R Wang, J Yang Advances in Neural Information Processing Systems 34, 8968-8983, 2021 | 9 | 2021 |
| Towards optimal statistical watermarking B Huang, B Zhu, H Zhu, JD Lee, J Jiao, MI Jordan arXiv preprint arXiv:2312.07930, 2023 | 5 | 2023 |
| InstaHide's Sample Complexity When Mixing Two Private Images B Huang, Z Song, R Tao, J Yin, R Zhang, D Zhuo arXiv preprint arXiv:2011.11877, 2020 | 5 | 2020 |
| Policy mirror descent for regularized reinforcement learning: A generalized framework with linear convergence, May 2021 W Zhan, S Cen, B Huang, Y Chen, JD Lee, Y Chi | 5 | |
| On Representation Complexity of Model-based and Model-free Reinforcement Learning H Zhu, B Huang, S Russell arXiv preprint arXiv:2310.01706, 2023 | 3 | 2023 |
| Sample complexity for quadratic bandits: hessian dependent bounds and optimal algorithms Q Yu, Y Wang, B Huang, Q Lei, JD Lee Advances in Neural Information Processing Systems 36, 2024 | 1 | 2024 |
| Optimal Sample Complexity Bounds for Non-convex Optimization under Kurdyka-Lojasiewicz Condition Q Yu, Y Wang, B Huang, Q Lei, JD Lee International Conference on Artificial Intelligence and Statistics, 6806-6821, 2023 | 1 | 2023 |
| Stochastic Zeroth-Order Optimization under Strongly Convexity and Lipschitz Hessian: Minimax Sample Complexity Q Yu, Y Wang, B Huang, Q Lei, JD Lee arXiv preprint arXiv:2406.19617, 2024 | | 2024 |
| Towards a Theoretical Understanding of the'Reversal Curse'via Training Dynamics H Zhu, B Huang, S Zhang, M Jordan, J Jiao, Y Tian, S Russell arXiv preprint arXiv:2405.04669, 2024 | | 2024 |
| Data Acquisition via Experimental Design for Decentralized Data Markets C Lu, B Huang, SP Karimireddy, P Vepakomma, M Jordan, R Raskar arXiv preprint arXiv:2403.13893, 2024 | | 2024 |
| Evaluating and Incentivizing Diverse Data Contributions in Collaborative Learning B Huang, SP Karimireddy, MI Jordan arXiv preprint arXiv:2306.05592, 2023 | | 2023 |
Jason D. LeeAssociate Professor of Electrical Engineering and Computer Science, Princeton University在 princeton.edu 的电子邮件经过验证
