Dhruv Rohatgi

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 35

Top Topics

High Dimensions

Partially Observable Markov

Reinforcement Learning

Top Venues

Electron. J. Comb.

Publications

Noah Golowich, Ankur Moitra, Dhruv Rohatgi
Exploration is Harder than Prediction: Cryptographically Separating Reinforcement Learning from Supervised Learning. CoRR (2024)
Noah Golowich, Ankur Moitra, Dhruv Rohatgi
Exploring and Learning in Sparse Linear MDPs without Computationally Intractable Oracles. STOC (2024)
Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi
Lasso with Latents: Efficient Estimation, Covariate Rescaling, and Computational-Statistical Gaps. COLT (2024)
Noah Golowich, Elad Hazan, Zhou Lu, Dhruv Rohatgi, Y. Jennifer Sun
Online Control in Population Dynamics. CoRR (2024)
Noah Golowich, Ankur Moitra, Dhruv Rohatgi
On Learning Parities with Dependent Noise. CoRR (2024)
Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi
Lasso with Latents: Efficient Estimation, Covariate Rescaling, and Computational-Statistical Gaps. CoRR (2024)
Chirag Pabbaraju, Dhruv Rohatgi, Anish Prasad Sevekari, Holden Lee, Ankur Moitra, Andrej Risteski
Provable benefits of score matching. NeurIPS (2023)
Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi
Feature Adaptation for Sparse Linear Regression. NeurIPS (2023)
Chirag Pabbaraju, Dhruv Rohatgi, Anish Prasad Sevekari, Holden Lee, Ankur Moitra, Andrej Risteski
Provable benefits of score matching. CoRR (2023)
Noah Golowich, Ankur Moitra, Dhruv Rohatgi
Planning and Learning in Partially Observable Systems via Filter Stability. STOC (2023)
Ankur Moitra, Dhruv Rohatgi
Provably Auditing Ordinary Least Squares in Low Dimensions. ICLR (2023)
Noah Golowich, Ankur Moitra, Dhruv Rohatgi
Exploring and Learning in Sparse Linear MDPs without Computationally Intractable Oracles. CoRR (2023)
Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi
Feature Adaptation for Sparse Linear Regression. CoRR (2023)
Noah Golowich, Ankur Moitra, Dhruv Rohatgi
Learning in Observable POMDPs, without Computationally Intractable Oracles. CoRR (2022)
Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi
Lower Bounds on Randomly Preconditioned Lasso via Robust Sparse Designs. NeurIPS (2022)
Noah Golowich, Ankur Moitra, Dhruv Rohatgi
Learning in Observable POMDPs, without Computationally Intractable Oracles. NeurIPS (2022)
Noah Golowich, Ankur Moitra, Dhruv Rohatgi
Planning in Observable POMDPs in Quasipolynomial Time. CoRR (2022)
Dhruv Rohatgi, Vasilis Syrgkanis
Robust Generalized Method of Moments: A Finite Sample Viewpoint. NeurIPS (2022)
Ankur Moitra, Dhruv Rohatgi
Provably Auditing Ordinary Least Squares in Low Dimensions. CoRR (2022)
Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi
Distributional Hardness Against Preconditioned Lasso via Erasure-Robust Designs. CoRR (2022)
Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi
On the Power of Preconditioning in Sparse Linear Regression. FOCS (2022)
Dhruv Rohatgi, John C. Urschel, Jake Wellens
Regarding Two Conjectures on Clique and Biclique Partitions. Electron. J. Comb. 28 (4) (2021)
Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi
On the Power of Preconditioning in Sparse Linear Regression. CoRR (2021)
Dhruv Rohatgi, Vasilis Syrgkanis
Robust Generalized Method of Moments: A Finite Sample Viewpoint. CoRR (2021)
Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi
On the Power of Preconditioning in Sparse Linear Regression. FOCS (2021)
Constantinos Daskalakis, Dhruv Rohatgi, Manolis Zampetakis
Constant-Expansion Suffices for Compressed Sensing with Generative Priors. CoRR (2020)
Constantinos Daskalakis, Dhruv Rohatgi, Emmanouil Zampetakis
Truncated Linear Regression in High Dimensions. NeurIPS (2020)
Dhruv Rohatgi
Near-Optimal Bounds for Online Caching with Machine Learned Advice. SODA (2020)
Constantinos Daskalakis, Dhruv Rohatgi, Manolis Zampetakis
Truncated Linear Regression in High Dimensions. CoRR (2020)
Constantinos Daskalakis, Dhruv Rohatgi, Emmanouil Zampetakis
Constant-Expansion Suffices for Compressed Sensing with Generative Priors. NeurIPS (2020)
Dhruv Rohatgi
Off-Diagonal Ordered Ramsey Numbers of Matchings. Electron. J. Comb. 26 (2) (2019)
Dhruv Rohatgi
Near-Optimal Bounds for Online Caching with Machine Learned Advice. CoRR (2019)
Dhruv Rohatgi
Conditional Hardness of Earth Mover Distance. CoRR (2019)
Dhruv Rohatgi
Conditional Hardness of Earth Mover Distance. APPROX-RANDOM (2019)
Dhruv Rohatgi
Sliding window order statistics in sublinear space. CoRR (2018)