| Towards Understanding Learning Representations: To What Extent Do Different Neural Networks Learn the Same Representation L Wang, L Hu, J Gu, Z Hu, Y Wu, K He, J Hopcroft Advances in Neural Information Processing Systems (NeurIPS) 2018, 9606-9615, 2018 | 107 | 2018 |
| Loss minimization through the lens of outcome indistinguishability P Gopalan, L Hu, MP Kim, O Reingold, U Wieder arXiv preprint arXiv:2210.08649, 2022 | 25 | 2022 |
| Quadratic upper bound for recursive teaching dimension of finite VC classes L Hu, R Wu, T Li, L Wang Conference on Learning Theory (COLT) 2017. arXiv preprint arXiv:1702.05677, 2017 | 23 | 2017 |
| Active tolerant testing A Blum, L Hu Conference On Learning Theory, 474-497, 2018 | 19 | 2018 |
| Near-Optimal Explainable k-Means for All Dimensions M Charikar, L Hu Proceedings of the 2022 Annual ACM-SIAM Symposium on Discrete Algorithms …, 2022 | 17 | 2022 |
| An Improved Local Search Algorithm for k-Median V Cohen-Addad, A Gupta, L Hu, H Oh, D Saulpic Proceedings of the 2022 Annual ACM-SIAM Symposium on Discrete Algorithms …, 2022 | 15 | 2022 |
| A unifying theory of distance from calibration J Błasiok, P Gopalan, L Hu, P Nakkiran Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 1727-1740, 2023 | 14 | 2023 |
| Robust and on-the-fly dataset denoising for image classification J Song, L Hu, Y Dauphin, M Auli, T Ma arXiv preprint arXiv:2003.10647, 2020 | 14 | 2020 |
| Omnipredictors for constrained optimization L Hu, IRL Navon, O Reingold, C Yang International Conference on Machine Learning, 13497-13527, 2023 | 13 | 2023 |
| Capacitated center problems with two-sided bounds and outliers H Ding, L Hu, L Huang, J Li Algorithms and Data Structures: 15th International Symposium, WADS 2017, St …, 2017 | 13 | 2017 |
| The Power of Many Samples in Query Complexity A Bassilakis, A Drucker, M Göös, L Hu, W Ma, LY Tan International Colloquium on Automata, Languages and Programming (ICALP), 2020 | 9 | 2020 |
| When Does Optimizing a Proper Loss Yield Calibration? J Blasiok, P Gopalan, L Hu, P Nakkiran Advances in Neural Information Processing Systems 36, 2024 | 6 | 2024 |
| Metric entropy duality and the sample complexity of outcome indistinguishability L Hu, C Peale, O Reingold International Conference on Algorithmic Learning Theory, 515-552, 2022 | 5 | 2022 |
| Approximation algorithms for orthogonal non-negative matrix factorization M Charikar, L Hu International Conference on Artificial Intelligence and Statistics, 2728-2736, 2021 | 5 | 2021 |
| Robust mean estimation on highly incomplete data with arbitrary outliers L Hu, O Reingold International Conference on Artificial Intelligence and Statistics, 1558-1566, 2021 | 4 | 2021 |
| Subspace recovery from heterogeneous data with non-isotropic noise JC Duchi, V Feldman, L Hu, K Talwar Advances in Neural Information Processing Systems 35, 5854-5866, 2022 | 3 | 2022 |
| Comparative learning: A sample complexity theory for two hypothesis classes L Hu, C Peale arXiv preprint arXiv:2211.09101, 2022 | 3 | 2022 |
| Loss minimization yields multicalibration for large neural networks J Błasiok, P Gopalan, L Hu, AT Kalai, P Nakkiran arXiv preprint arXiv:2304.09424, 2023 | 2 | 2023 |
| Predict to Minimize Swap Regret for All Payoff-Bounded Tasks L Hu, Y Wu arXiv preprint arXiv:2404.13503, 2024 | | 2024 |
| Testing Calibration in Subquadratic Time L Hu, K Tian, C Yang arXiv preprint arXiv:2402.13187, 2024 | | 2024 |
Parikshit GopalanApple在 apple.com 的电子邮件经过验证
