Dhruv Rohatgi - RankMe

50 papers A* 20Journal 29Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Reject, Resample, Repeat: Understanding Parallel Reasoning in Language Model Inference. CoRR Noah Golowich, Fan Chen, Dhruv Rohatgi, Raghav Singhal, Carles Domingo-Enrich, Dylan J. Foster, Akshay Krishnamurthy
2026	J	`jnl`	Steering diffusion models with quadratic rewards: a fine-grained analysis. CoRR Ankur Moitra, Andrej Risteski, Dhruv Rohatgi
2025	A*	`conf`	Computational-Statistical Tradeoffs at the Next-Token Prediction Barrier: Autoregressive and Imitation Learning under Misspecification (extended abstract). COLT Dhruv Rohatgi, Adam Block, Audrey Huang, Akshay Krishnamurthy, Dylan J. Foster
2025	J	`jnl`	Computational-Statistical Tradeoffs at the Next-Token Prediction Barrier: Autoregressive and Imitation Learning under Misspecification. CoRR Dhruv Rohatgi, Adam Block, Audrey Huang, Akshay Krishnamurthy, Dylan J. Foster
2025	A*	`conf`	Is a Good Foundation Necessary for Efficient Reinforcement Learning? The Computational Role of the Base Model in Exploration. COLT Dylan J. Foster, Zakaria Mhammedi, Dhruv Rohatgi
2025	J	`jnl`	Is a Good Foundation Necessary for Efficient Reinforcement Learning? The Computational Role of the Base Model in Exploration. CoRR Dylan J. Foster, Zakaria Mhammedi, Dhruv Rohatgi
2025	J	`jnl`	Necessary and Sufficient Oracles: Toward a Computational Taxonomy For Reinforcement Learning. CoRR Dhruv Rohatgi, Dylan J. Foster
2025	A*	`conf`	Necessary and Sufficient Oracles: Toward a Computational Taxonomy for Reinforcement Learning. COLT Dhruv Rohatgi, Dylan J. Foster
2025	A*	`conf`	Self-Improvement in Language Models: The Sharpening Mechanism. ICLR Audrey Huang, Adam Block, Dylan J. Foster, Dhruv Rohatgi, Cyril Zhang, Max Simchowitz, Jordan T. Ash, Akshay Krishnamurthy
2025	J	`jnl`	Taming Imperfect Process Verifiers: A Sampling Perspective on Backtracking. CoRR Dhruv Rohatgi, Abhishek Shetty, Donya Saless, Yuchen Li, Ankur Moitra, Andrej Risteski, Dylan J. Foster
2025	J	`jnl`	To Distill or Decide? Understanding the Algorithmic Trade-off in Partially Observable Reinforcement Learning. CoRR Yuda Song, Dhruv Rohatgi, Aarti Singh, J. Andrew Bagnell
2025	A*	`conf`	Towards characterizing the value of edge embeddings in Graph Neural Networks. ICML Dhruv Rohatgi, Tanya Marwah, Zachary Chase Lipton, Jianfeng Lu, Ankur Moitra, Andrej Risteski
2024	A*	`conf`	Exploration is Harder than Prediction: Cryptographically Separating Reinforcement Learning from Supervised Learning. FOCS Noah Golowich, Ankur Moitra, Dhruv Rohatgi
2024	J	`jnl`	Exploration is Harder than Prediction: Cryptographically Separating Reinforcement Learning from Supervised Learning. CoRR Noah Golowich, Ankur Moitra, Dhruv Rohatgi
2024	A*	`conf`	Exploring and Learning in Sparse Linear MDPs without Computationally Intractable Oracles. STOC Noah Golowich, Ankur Moitra, Dhruv Rohatgi
2024	A*	`conf`	Lasso with Latents: Efficient Estimation, Covariate Rescaling, and Computational-Statistical Gaps. COLT Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi
2024	J	`jnl`	Lasso with Latents: Efficient Estimation, Covariate Rescaling, and Computational-Statistical Gaps. CoRR Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi
2024	J	`jnl`	On Learning Parities with Dependent Noise. CoRR Noah Golowich, Ankur Moitra, Dhruv Rohatgi
2024	A*	`conf`	Online Control in Population Dynamics. NeurIPS Noah Golowich, Elad Hazan, Zhou Lu, Dhruv Rohatgi, Y. Jennifer Sun
2024	J	`jnl`	Online Control in Population Dynamics. CoRR Noah Golowich, Elad Hazan, Zhou Lu, Dhruv Rohatgi, Y. Jennifer Sun
2024	J	`jnl`	Self-Improvement in Language Models: The Sharpening Mechanism. CoRR Audrey Huang, Adam Block, Dylan J. Foster, Dhruv Rohatgi, Cyril Zhang, Max Simchowitz, Jordan T. Ash, Akshay Krishnamurthy
2024	J	`jnl`	Towards characterizing the value of edge embeddings in Graph Neural Networks. CoRR Dhruv Rohatgi, Tanya Marwah, Zachary Chase Lipton, Jianfeng Lu, Ankur Moitra, Andrej Risteski
2023	J	`jnl`	Exploring and Learning in Sparse Linear MDPs without Computationally Intractable Oracles. CoRR Noah Golowich, Ankur Moitra, Dhruv Rohatgi
2023	A*	`conf`	Feature Adaptation for Sparse Linear Regression. NeurIPS Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi
2023	J	`jnl`	Feature Adaptation for Sparse Linear Regression. CoRR Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi
2023	A*	`conf`	Planning and Learning in Partially Observable Systems via Filter Stability. STOC Noah Golowich, Ankur Moitra, Dhruv Rohatgi
2023	A*	`conf`	Provable benefits of score matching. NeurIPS Chirag Pabbaraju, Dhruv Rohatgi, Anish Prasad Sevekari, Holden Lee, Ankur Moitra, Andrej Risteski
2023	J	`jnl`	Provable benefits of score matching. CoRR Chirag Pabbaraju, Dhruv Rohatgi, Anish Prasad Sevekari, Holden Lee, Ankur Moitra, Andrej Risteski
2023	A*	`conf`	Provably Auditing Ordinary Least Squares in Low Dimensions. ICLR Ankur Moitra, Dhruv Rohatgi
2022	J	`jnl`	Distributional Hardness Against Preconditioned Lasso via Erasure-Robust Designs. CoRR Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi
2022	A*	`conf`	Learning in Observable POMDPs, without Computationally Intractable Oracles. NeurIPS Noah Golowich, Ankur Moitra, Dhruv Rohatgi
2022	J	`jnl`	Learning in Observable POMDPs, without Computationally Intractable Oracles. CoRR Noah Golowich, Ankur Moitra, Dhruv Rohatgi
2022	A*	`conf`	Lower Bounds on Randomly Preconditioned Lasso via Robust Sparse Designs. NeurIPS Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi
2022	J	`jnl`	Planning in Observable POMDPs in Quasipolynomial Time. CoRR Noah Golowich, Ankur Moitra, Dhruv Rohatgi
2022	J	`jnl`	Provably Auditing Ordinary Least Squares in Low Dimensions. CoRR Ankur Moitra, Dhruv Rohatgi
2022	A*	`conf`	Robust Generalized Method of Moments: A Finite Sample Viewpoint. NeurIPS Dhruv Rohatgi, Vasilis Syrgkanis
2021	A*	`conf`	On the Power of Preconditioning in Sparse Linear Regression. FOCS Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi
2021	J	`jnl`	On the Power of Preconditioning in Sparse Linear Regression. CoRR Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi
2021	J	`jnl`	Regarding Two Conjectures on Clique and Biclique Partitions. Electron. J. Comb. Dhruv Rohatgi, John C. Urschel, Jake Wellens
2021	J	`jnl`	Robust Generalized Method of Moments: A Finite Sample Viewpoint. CoRR Dhruv Rohatgi, Vasilis Syrgkanis
2020	A*	`conf`	Constant-Expansion Suffices for Compressed Sensing with Generative Priors. NeurIPS Constantinos Daskalakis, Dhruv Rohatgi, Emmanouil Zampetakis
2020	J	`jnl`	Constant-Expansion Suffices for Compressed Sensing with Generative Priors. CoRR Constantinos Daskalakis, Dhruv Rohatgi, Manolis Zampetakis
2020	A*	`conf`	Near-Optimal Bounds for Online Caching with Machine Learned Advice. SODA Dhruv Rohatgi
2020	A*	`conf`	Truncated Linear Regression in High Dimensions. NeurIPS Constantinos Daskalakis, Dhruv Rohatgi, Emmanouil Zampetakis
2020	J	`jnl`	Truncated Linear Regression in High Dimensions. CoRR Constantinos Daskalakis, Dhruv Rohatgi, Manolis Zampetakis
2019	—	`conf`	Conditional Hardness of Earth Mover Distance. APPROX-RANDOM Dhruv Rohatgi
2019	J	`jnl`	Conditional Hardness of Earth Mover Distance. CoRR Dhruv Rohatgi
2019	J	`jnl`	Near-Optimal Bounds for Online Caching with Machine Learned Advice. CoRR Dhruv Rohatgi
2019	J	`jnl`	Off-Diagonal Ordered Ramsey Numbers of Matchings. Electron. J. Comb. Dhruv Rohatgi
2018	J	`jnl`	Sliding window order statistics in sublinear space. CoRR Dhruv Rohatgi