Near-optimal bounds for online caching with machine learned advice D Rohatgi Proceedings of the Fourteenth Annual ACM-SIAM Symposium on Discrete …, 2020 | 173 | 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 | 41* | 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 | 40 | 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 | 23 | 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 | 20 | 2020 |
Truncated linear regression in high dimensions C Daskalakis, D Rohatgi, E Zampetakis Advances in Neural Information Processing Systems 33, 10338-10347, 2020 | 14 | 2020 |
Conditional hardness of earth mover distance D Rohatgi 22nd Intl. Conference on Approximation Algorithms for Combinatorial …, 2019 | 14 | 2019 |
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 | 13 | 2024 |
Off-diagonal ordered Ramsey numbers of matchings D Rohatgi arXiv preprint arXiv:1808.04025, 2018 | 9 | 2018 |
Feature adaptation for sparse linear regression J Kelner, F Koehler, R Meka, D Rohatgi Advances in Neural Information Processing Systems 36, 2024 | 7 | 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 | 7* | 2022 |
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 | 6 | 2024 |
Provably auditing ordinary least squares in low dimensions A Moitra, D Rohatgi arXiv preprint arXiv:2205.14284, 2022 | 6 | 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 | 5 | 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 | 3 | 2022 |
Online Control in Population Dynamics N Golowich, E Hazan, Z Lu, D Rohatgi, YJ Sun arXiv preprint arXiv:2406.01799, 2024 | 1 | 2024 |
Computationally Efficient Reinforcement Learning under Partial Observability D Rohatgi Massachusetts Institute of Technology, 2023 | 1 | 2023 |
Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2019) V Fernández, CN Chou, Z Lei, P Nakkiran, B Moseley, M Sviridenko, ... Schloss Dagstuhl-Leibniz-Zentrum für Informatik GmbH, 2019 | 1 | 2019 |
Necessary and Sufficient Oracles: Toward a Computational Taxonomy For Reinforcement Learning D Rohatgi, DJ Foster arXiv preprint arXiv:2502.08632, 2025 | | 2025 |