Dipendra Misra

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 47

Top Topics

Reinforcement Learning

Lipschitz Continuity

Inverse Dynamics

Top Venues

Publications

Dipendra Misra, Aldo Pacchiano, Robert E. Schapire
Provable Interactive Learning with Hindsight Instruction Feedback. CoRR (2024)
Jonathan D. Chang, Wenhao Zhan, Owen Oertell, Kianté Brantley, Dipendra Misra, Jason D. Lee, Wen Sun
Dataset Reset Policy Optimization for RLHF. CoRR (2024)
Dipendra Misra, Akanksha Saran, Tengyang Xie, Alex Lamb, John Langford
Towards Principled Representation Learning from Videos for Reinforcement Learning. ICLR (2024)
Pratyusha Sharma, Jordan T. Ash, Dipendra Misra
The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction. ICLR (2024)
Ge Gao, Alexey Taymanov, Eduardo Salinas, Paul Mineiro, Dipendra Misra
Aligning LLM Agents by Learning Latent Preference from User Edits. CoRR (2024)
Dipendra Misra, Akanksha Saran, Tengyang Xie, Alex Lamb, John Langford
Towards Principled Representation Learning from Videos for Reinforcement Learning. CoRR (2024)
Victor Zhong, Dipendra Misra, Xingdi Yuan, Marc-Alexandre Côté
Policy Improvement using Language Feedback Models. CoRR (2024)
Dylan J. Foster, Adam Block, Dipendra Misra
Is Behavior Cloning All You Need? Understanding Horizon in Imitation Learning. CoRR (2024)
Anqi Li, Dipendra Misra, Andrey Kolobov, Ching-An Cheng
Survival Instinct in Offline Reinforcement Learning. CoRR (2023)
Andrew Bennett, Dipendra Misra, Nathan Kallus
Provable Safe Reinforcement Learning with Binary Feedback. AISTATS (2023)
Ching-An Cheng, Andrey Kolobov, Dipendra Misra, Allen Nie, Adith Swaminathan
LLF-Bench: Benchmark for Interactive Learning from Language Feedback. CoRR (2023)
Anqi Li, Dipendra Misra, Andrey Kolobov, Ching-An Cheng
Survival Instinct in Offline Reinforcement Learning. NeurIPS (2023)
Pratyusha Sharma, Jordan T. Ash, Dipendra Misra
The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction. CoRR (2023)
Alex Lamb, Riashat Islam, Yonathan Efroni, Aniket Rajiv Didolkar, Dipendra Misra, Dylan J. Foster, Lekan P. Molu, Rajan Chari, Akshay Krishnamurthy, John Langford
Guaranteed Discovery of Control-Endogenous Latent States with Multi-Step Inverse Models. Trans. Mach. Learn. Res. 2023 (2023)
Riashat Islam, Manan Tomar, Alex Lamb, Yonathan Efroni, Hongyu Zang, Aniket Rajiv Didolkar, Dipendra Misra, Xin Li, Harm van Seijen, Remi Tachet des Combes, John Langford
Principled Offline RL in the Presence of Rich Exogenous Information. ICML (2023)
Jonathan D. Chang, Kianté Brantley, Rajkumar Ramamurthy, Dipendra Misra, Wen Sun
Learning to Generate Better Than Your LLM. CoRR (2023)
Nikunj Saunshi, Jordan T. Ash, Surbhi Goel, Dipendra Misra, Cyril Zhang, Sanjeev Arora, Sham M. Kakade, Akshay Krishnamurthy
Understanding Contrastive Learning Requires Incorporating Inductive Biases. CoRR (2022)
Yonathan Efroni, Dylan J. Foster, Dipendra Misra, Akshay Krishnamurthy, John Langford
Sample-Efficient Reinforcement Learning in the Presence of Exogenous Information. CoRR (2022)
Alex Lamb, Riashat Islam, Yonathan Efroni, Aniket Didolkar, Dipendra Misra, Dylan J. Foster, Lekan Molu, Rajan Chari, Akshay Krishnamurthy, John Langford
Guaranteed Discovery of Controllable Latent States with Multi-Step Inverse Models. CoRR (2022)
Yao Liu, Dipendra Misra, Miro Dudík, Robert E. Schapire
Provably Sample-Efficient RL with Side Information about Latent Dynamics. CoRR (2022)
Riashat Islam, Manan Tomar, Alex Lamb, Yonathan Efroni, Hongyu Zang, Aniket Didolkar, Dipendra Misra, Xin Li, Harm van Seijen, Remi Tachet des Combes, John Langford
Agent-Controller Representations: Principled Offline RL with Rich Exogenous Information. CoRR (2022)
Nikunj Saunshi, Jordan T. Ash, Surbhi Goel, Dipendra Misra, Cyril Zhang, Sanjeev Arora, Sham M. Kakade, Akshay Krishnamurthy
Understanding Contrastive Learning Requires Incorporating Inductive Biases. ICML (2022)
Andrew Bennett, Dipendra Misra, Nathan Kallus
Provable Safe Reinforcement Learning with Binary Feedback. CoRR (2022)
Shengpu Tang, Felipe Vieira Frujeri, Dipendra Misra, Alex Lamb, John Langford, Paul Mineiro, Sebastian Kochman
Towards Data-Driven Offline Simulations for Online Reinforcement Learning. CoRR (2022)
Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Dipendra Misra
Investigating the Role of Negatives in Contrastive Representation Learning. AISTATS (2022)
Yonathan Efroni, Dylan J. Foster, Dipendra Misra, Akshay Krishnamurthy, John Langford
Sample-Efficient Reinforcement Learning in the Presence of Exogenous Information. COLT (2022)
Yao Liu, Dipendra Misra, Miro Dudík, Robert E. Schapire
Provably sample-efficient RL with side information about latent dynamics. NeurIPS (2022)
Yonathan Efroni, Dipendra Misra, Akshay Krishnamurthy, Alekh Agarwal, John Langford
Provably Filtering Exogenous Distractors using Multistep Inverse Dynamics. ICLR (2022)
Khanh Nguyen, Dipendra Misra, Robert E. Schapire, Miroslav Dudík, Patrick Shafto
Interactive Learning from Activity Description. ICML (2021)
Yonathan Efroni, Dipendra Misra, Akshay Krishnamurthy, Alekh Agarwal, John Langford
Provable RL with Exogenous Distractors via Multistep Inverse Dynamics. CoRR (2021)
Andrew Bennett, Dipendra Misra, Nga Than
Have you tried Neural Topic Models? Comparative Analysis of Neural and Non-Neural Topic Models with Application to COVID-19 Twitter Data. CoRR (2021)
Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Dipendra Misra
Investigating the Role of Negatives in Contrastive Representation Learning. CoRR (2021)
Dipendra Misra, Qinghua Liu, Chi Jin, John Langford
Provable Rich Observation Reinforcement Learning with Combinatorial Latent States. ICLR (2021)
Khanh Nguyen, Dipendra Misra, Robert E. Schapire, Miroslav Dudík, Patrick Shafto
Interactive Learning from Activity Description. CoRR (2021)
Zakaria Mhammedi, Dylan J. Foster, Max Simchowitz, Dipendra Misra, Wen Sun, Akshay Krishnamurthy, Alexander Rakhlin, John Langford
Learning the Linear Quadratic Regulator from Nonlinear Observations. CoRR (2020)
Dipendra Misra, Mikael Henaff, Akshay Krishnamurthy, John Langford
Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning. ICML (2020)
Zakaria Mhammedi, Dylan J. Foster, Max Simchowitz, Dipendra Misra, Wen Sun, Akshay Krishnamurthy, Alexander Rakhlin, John Langford
Learning the Linear Quadratic Regulator from Nonlinear Observations. NeurIPS (2020)
Kavosh Asadi, Dipendra Misra, Seungchan Kim, Michael L. Littman
Combating the Compounding-Error Problem with a Multi-step Model. CoRR (2019)
Aaron Walsman, Yonatan Bisk, Saadia Gabriel, Dipendra Misra, Yoav Artzi, Yejin Choi, Dieter Fox
EARLY FUSION for Goal Directed Robotic Vision. IROS (2019)
Howard Chen, Alane Suhr, Dipendra Misra, Noah Snavely, Yoav Artzi
TOUCHDOWN: Natural Language Navigation and Spatial Reasoning in Visual Street Environments. CVPR (2019)
Dipendra Misra, Mikael Henaff, Akshay Krishnamurthy, John Langford
Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning. CoRR (2019)
Kavosh Asadi, Evan Cater, Dipendra Misra, Michael L. Littman
Towards a Simple Approach to Multi-step Model-based Reinforcement Learning. CoRR (2018)
Dipendra Misra, Ming-Wei Chang, Xiaodong He, Wen-tau Yih
Policy Shaping and Generalized Update Equations for Semantic Parsing from Denotations. CoRR (2018)
Kavosh Asadi, Dipendra Misra, Michael L. Littman
Lipschitz Continuity in Model-based Reinforcement Learning. ICML (2018)
Dipendra Misra, Ming-Wei Chang, Xiaodong He, Wen-tau Yih
Policy Shaping and Generalized Update Equations for Semantic Parsing from Denotations. EMNLP (2018)
Kavosh Asadi, Dipendra Misra, Michael L. Littman
Lipschitz Continuity in Model-based Reinforcement Learning. CoRR (2018)
Kavosh Asadi, Evan Cater, Dipendra Misra, Michael L. Littman
Equivalence Between Wasserstein and Value-Aware Model-based Reinforcement Learning. CoRR (2018)