Dhruv Rohatgi

Hi! I'm a third-year graduate student in EECS at MIT. I'm very fortunate to be advised by Ankur Moitra. My current research interests are in computational statistics and reinforcement learning theory.

I am grateful to be supported by an NDSEG Fellowship. In 2021-2022, I was also supported by an MIT Akamai Presidential Fellowship.

To reach me: [first initial][last name]@mit.edu

Publications and Preprints

1. Exploration is Harder than Prediction: Cryptographically Separating Reinforcement Learning from Supervised Learning
   with Ankur Moitra and Noah Golowich
   
   [arXiv:2404.03774]
2. Lasso with Latents: Efficient Estimation, Covariate Rescaling, and Computational-Statistical Gaps
   with Jonathan Kelner, Frederic Koehler, and Raghu Meka
   
   [arXiv:2402.15409]
3. Exploring and Learning in Sparse Linear MDPs without Computationally Intractable Oracles
   with Ankur Moitra and Noah Golowich
   
   STOC 2024 ♦ 56th Annual ACM Symposium on Theory of Computing (to appear).
   [arXiv:2309.09457]
4. Provable Benefits of Score Matching
   with Chirag Pabbaraju, Anish Sevekari, Holden Lee, Ankur Moitra, and Andrej Risteski
   
   NeurIPS 2023 (Spotlight Presentation) ♦ 37th Conference on Neural Information Processing Systems (to appear).
   [arXiv:2306.01993]
5. Feature Adaptation for Sparse Linear Regression
   with Jonathan Kelner, Frederic Koehler, and Raghu Meka
   
   NeurIPS 2023 (Spotlight Presentation) ♦ 37th Conference on Neural Information Processing Systems (to appear).
   [arXiv:2305.16892]
6. Learning in Observable POMDPs, without Computationally Intractable Oracles
   with Ankur Moitra and Noah Golowich
   
   NeurIPS 2022 ♦ 36th Conference on Neural Information Processing Systems.
   [arXiv:2206.03446] [Conference]
7. Provably Auditing Ordinary Least Squares in Low Dimensions
   with Ankur Moitra
   
   ICLR 2023 ♦ 11th International Conference on Learning Representations.
   [arXiv:2205.14284] [Conference]
8. Distributional Hardness Against Preconditioned Lasso via Erasure-Robust Designs
   with Jonathan Kelner, Frederic Koehler, and Raghu Meka
   
   NeurIPS 2022 ♦ 36th Conference on Neural Information Processing Systems.
   [arXiv:2203.02824] [Conference]
9. Planning in Observable POMDPs in Quasipolynomial Time
   with Ankur Moitra and Noah Golowich
   
   STOC 2023 ♦ 55th Annual ACM Symposium on Theory of Computing.
   [arXiv:2201.04735] [Conference]
10. Robust Generalized Method of Moments: A Finite Sample Viewpoint
    with Vasilis Syrgkanis
    
    Preliminary version selected for Oral Presentation at MLECON Workshop (NeurIPS 2021)
    NeurIPS 2022 ♦ 36th Conference on Neural Information Processing Systems.
    [arXiv:2110.03070] [Conference]
11. On the Power of Preconditioning in Sparse Linear Regression
    with Jonathan Kelner, Frederic Koehler, and Raghu Meka
    
    FOCS 2021 ♦ 62nd Annual IEEE Symposium on Foundations of Computer Science.
    [arXiv:2106.09207] [Conference]
12. Truncated Linear Regression in High Dimensions
    with Costis Daskalakis and Manolis Zampetakis
    NeurIPS 2020 ♦ 34th Conference on Neural Information Processing Systems.
    [arXiv:2007.14539] [Conference]
13. Constant-Expansion Suffices for Compressed Sensing with Generative Priors
    with Costis Daskalakis and Manolis Zampetakis
    NeurIPS 2020 (Spotlight Presentation) ♦ 34th Conference on Neural Information Processing Systems.
    [arXiv:2006.04237] [Conference]
14. Regarding two conjectures on clique and biclique partitions
    with John C. Urschel and Jake Wellens
    The Electronic Journal of Combinatorics (2021).
    [arXiv:2005.02529] [Journal]
15. Near-Optimal Bounds for Online Caching with Machine-Learned Advice
    SODA 2020 ♦ 31st ACM-SIAM Symposium on Discrete Algorithms.
    [arXiv:1910.12172] [Conference]
16. Conditional Hardness for Approximate Earth Mover Distance
    APPROX 2019 ♦ 22nd Intl. Conference on Approximation Algorithms for Combinatorial Optimization Problems.
    [arXiv:1909.11068] [Conference]
17. Off-diagonal Ordered Ramsey Numbers of Matchings
    The Electronic Journal of Combinatorics (2019).
    [arXiv:1808.04025] [Journal]

Website design adapted from Frederic Koehler and Manolis Zampetakis.