| Near-optimal bounds for online caching with machine learned advice D Rohatgi Proceedings of the Fourteenth Annual ACM-SIAM Symposium on Discrete …, 2020 | 162 | 2020 |
| Planning and learning in partially observable systems via filter stability N Golowich, A Moitra, D Rohatgi Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 349-362, 2023 | 38* | 2023 |
| Learning in observable pomdps, without computationally intractable oracles N Golowich, A Moitra, D Rohatgi Advances in neural information processing systems 35, 1458-1473, 2022 | 34 | 2022 |
| On the power of preconditioning in sparse linear regression JA Kelner, F Koehler, R Meka, D Rohatgi 2021 IEEE 62nd Annual Symposium on Foundations of Computer Science (FOCS …, 2022 | 21 | 2022 |
| Constant-expansion suffices for compressed sensing with generative priors C Daskalakis, D Rohatgi, E Zampetakis Advances in Neural Information Processing Systems 33, 13917-13926, 2020 | 17 | 2020 |
| Conditional hardness of earth mover distance D Rohatgi 22nd Intl. Conference on Approximation Algorithms for Combinatorial …, 2019 | 13 | 2019 |
| Truncated linear regression in high dimensions C Daskalakis, D Rohatgi, E Zampetakis Advances in Neural Information Processing Systems 33, 10338-10347, 2020 | 12 | 2020 |
| Provable benefits of score matching C Pabbaraju, D Rohatgi, AP Sevekari, H Lee, A Moitra, A Risteski Advances in Neural Information Processing Systems 36, 2024 | 8 | 2024 |
| Lower bounds on randomly preconditioned lasso via robust sparse designs J Kelner, F Koehler, R Meka, D Rohatgi Advances in neural information processing systems 35, 24419-24431, 2022 | 6* | 2022 |
| Off-diagonal ordered Ramsey numbers of matchings D Rohatgi arXiv preprint arXiv:1808.04025, 2018 | 6 | 2018 |
| Exploring and learning in sparse linear mdps without computationally intractable oracles N Golowich, A Moitra, D Rohatgi Proceedings of the 56th Annual ACM Symposium on Theory of Computing, 183-193, 2024 | 5 | 2024 |
| Provably auditing ordinary least squares in low dimensions A Moitra, D Rohatgi arXiv preprint arXiv:2205.14284, 2022 | 5 | 2022 |
| Exploration is harder than prediction: Cryptographically separating reinforcement learning from supervised learning N Golowich, A Moitra, D Rohatgi arXiv preprint arXiv:2404.03774, 2024 | 4 | 2024 |
| Feature adaptation for sparse linear regression J Kelner, F Koehler, R Meka, D Rohatgi Advances in Neural Information Processing Systems 36, 2024 | 4 | 2024 |
| Regarding two questions about clique and biclique partitions D Rohatgi, JC Urschel, J Wellens Electron. J. Comb 28 (4), 2021 | 4* | 2021 |
| Robust generalized method of moments: a finite sample viewpoint D Rohatgi, V Syrgkanis Advances in Neural Information Processing Systems 35, 15970-15981, 2022 | 2 | 2022 |
| Computationally Efficient Reinforcement Learning under Partial Observability D Rohatgi Massachusetts Institute of Technology, 2023 | 1 | 2023 |
| Online Control in Population Dynamics N Golowich, E Hazan, Z Lu, D Rohatgi, YJ Sun arXiv preprint arXiv:2406.01799, 2024 | | 2024 |
| On Learning Parities with Dependent Noise N Golowich, A Moitra, D Rohatgi arXiv preprint arXiv:2404.11325, 2024 | | 2024 |
| Lasso with Latents: Efficient Estimation, Covariate Rescaling, and Computational-Statistical Gaps J Kelner, F Koehler, R Meka, D Rohatgi arXiv preprint arXiv:2402.15409, 2024 | | 2024 |
