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Dhruv Rohatgi
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Near-optimal bounds for online caching with machine learned advice
D Rohatgi
Proceedings of the Fourteenth Annual ACM-SIAM Symposium on Discrete …, 2020
1732020
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
402022
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
232022
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
202020
Truncated linear regression in high dimensions
C Daskalakis, D Rohatgi, E Zampetakis
Advances in Neural Information Processing Systems 33, 10338-10347, 2020
142020
Conditional hardness of earth mover distance
D Rohatgi
22nd Intl. Conference on Approximation Algorithms for Combinatorial …, 2019
142019
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
132024
Off-diagonal ordered Ramsey numbers of matchings
D Rohatgi
arXiv preprint arXiv:1808.04025, 2018
92018
Feature adaptation for sparse linear regression
J Kelner, F Koehler, R Meka, D Rohatgi
Advances in Neural Information Processing Systems 36, 2024
72024
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
62024
Provably auditing ordinary least squares in low dimensions
A Moitra, D Rohatgi
arXiv preprint arXiv:2205.14284, 2022
62022
Exploration is harder than prediction: Cryptographically separating reinforcement learning from supervised learning
N Golowich, A Moitra, D Rohatgi
arXiv preprint arXiv:2404.03774, 2024
52024
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
32022
Online Control in Population Dynamics
N Golowich, E Hazan, Z Lu, D Rohatgi, YJ Sun
arXiv preprint arXiv:2406.01799, 2024
12024
Computationally Efficient Reinforcement Learning under Partial Observability
D Rohatgi
Massachusetts Institute of Technology, 2023
12023
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
12019
Necessary and Sufficient Oracles: Toward a Computational Taxonomy For Reinforcement Learning
D Rohatgi, DJ Foster
arXiv preprint arXiv:2502.08632, 2025
2025
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Articles 1–20