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Dipendra Misra
Person information
- affiliation: Cornell University, NY, USA
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Books and Theses
- 2019
- [b1]Dipendra Misra:
Scalable and Interpretable Approaches for Learning to Follow Natural Language Instructions. Cornell University, USA, 2019
Journal Articles
- 2023
- [j2]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) - 2016
- [j1]Dipendra Kumar Misra, Jaeyong Sung, Kevin Lee, Ashutosh Saxena:
Tell me Dave: Context-sensitive grounding of natural language to manipulation instructions. Int. J. Robotics Res. 35(1-3): 281-300 (2016)
Conference and Workshop Papers
- 2024
- [c25]Dipendra Misra, Akanksha Saran, Tengyang Xie, Alex Lamb, John Langford:
Towards Principled Representation Learning from Videos for Reinforcement Learning. ICLR 2024 - [c24]Pratyusha Sharma, Jordan T. Ash, Dipendra Misra:
The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction. ICLR 2024 - [c23]Dipendra Misra, Aldo Pacchiano, Robert E. Schapire:
Provable Interactive Learning with Hindsight Instruction Feedback. ICML 2024 - 2023
- [c22]Andrew Bennett, Dipendra Misra, Nathan Kallus:
Provable Safe Reinforcement Learning with Binary Feedback. AISTATS 2023: 10871-10900 - [c21]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: 14390-14421 - [c20]Anqi Li, Dipendra Misra, Andrey Kolobov, Ching-An Cheng:
Survival Instinct in Offline Reinforcement Learning. NeurIPS 2023 - 2022
- [c19]Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Dipendra Misra:
Investigating the Role of Negatives in Contrastive Representation Learning. AISTATS 2022: 7187-7209 - [c18]Yonathan Efroni, Dylan J. Foster, Dipendra Misra, Akshay Krishnamurthy, John Langford:
Sample-Efficient Reinforcement Learning in the Presence of Exogenous Information. COLT 2022: 5062-5127 - [c17]Yonathan Efroni, Dipendra Misra, Akshay Krishnamurthy, Alekh Agarwal, John Langford:
Provably Filtering Exogenous Distractors using Multistep Inverse Dynamics. ICLR 2022 - [c16]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: 19250-19286 - [c15]Yao Liu, Dipendra Misra, Miro Dudík, Robert E. Schapire:
Provably sample-efficient RL with side information about latent dynamics. NeurIPS 2022 - 2021
- [c14]Dipendra Misra, Qinghua Liu, Chi Jin, John Langford:
Provable Rich Observation Reinforcement Learning with Combinatorial Latent States. ICLR 2021 - [c13]Khanh Nguyen, Dipendra Misra, Robert E. Schapire, Miroslav Dudík, Patrick Shafto:
Interactive Learning from Activity Description. ICML 2021: 8096-8108 - 2020
- [c12]Dipendra Misra, Mikael Henaff, Akshay Krishnamurthy, John Langford:
Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning. ICML 2020: 6961-6971 - [c11]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 - 2019
- [c10]Howard Chen, Alane Suhr, Dipendra Misra, Noah Snavely, Yoav Artzi:
TOUCHDOWN: Natural Language Navigation and Spatial Reasoning in Visual Street Environments. CVPR 2019: 12538-12547 - [c9]Aaron Walsman, Yonatan Bisk, Saadia Gabriel, Dipendra Misra, Yoav Artzi, Yejin Choi, Dieter Fox:
EARLY FUSION for Goal Directed Robotic Vision. IROS 2019: 1025-1031 - 2018
- [c8]Valts Blukis, Dipendra Kumar Misra, Ross A. Knepper, Yoav Artzi:
Mapping Navigation Instructions to Continuous Control Actions with Position-Visitation Prediction. CoRL 2018: 505-518 - [c7]Dipendra Misra, Ming-Wei Chang, Xiaodong He, Wen-tau Yih:
Policy Shaping and Generalized Update Equations for Semantic Parsing from Denotations. EMNLP 2018: 2442-2452 - [c6]Dipendra Kumar Misra, Andrew Bennett, Valts Blukis, Eyvind Niklasson, Max Shatkhin, Yoav Artzi:
Mapping Instructions to Actions in 3D Environments with Visual Goal Prediction. EMNLP 2018: 2667-2678 - [c5]Kavosh Asadi, Dipendra Misra, Michael L. Littman:
Lipschitz Continuity in Model-based Reinforcement Learning. ICML 2018: 264-273 - 2017
- [c4]Dipendra Kumar Misra, John Langford, Yoav Artzi:
Mapping Instructions and Visual Observations to Actions with Reinforcement Learning. EMNLP 2017: 1004-1015 - 2016
- [c3]Dipendra Kumar Misra, Yoav Artzi:
Neural Shift-Reduce CCG Semantic Parsing. EMNLP 2016: 1775-1786 - 2015
- [c2]Dipendra Kumar Misra, Kejia Tao, Percy Liang, Ashutosh Saxena:
Environment-Driven Lexicon Induction for High-Level Instructions. ACL (1) 2015: 992-1002 - 2014
- [c1]Dipendra Kumar Misra, Jaeyong Sung, Kevin Lee, Ashutosh Saxena:
Tell Me Dave: Context-Sensitive Grounding of Natural Language to Manipulation Instructions. Robotics: Science and Systems 2014
Editorship
- 2018
- [e1]Isabelle Augenstein, Kris Cao, He He, Felix Hill, Spandana Gella, Jamie Kiros, Hongyuan Mei, Dipendra Misra:
Proceedings of The Third Workshop on Representation Learning for NLP, Rep4NLP@ACL 2018, Melbourne, Australia, July 20, 2018. Association for Computational Linguistics 2018, ISBN 978-1-948087-43-8 [contents]
Informal and Other Publications
- 2024
- [i35]Victor Zhong, Dipendra Misra, Xingdi Yuan, Marc-Alexandre Côté:
Policy Improvement using Language Feedback Models. CoRR abs/2402.07876 (2024) - [i34]Dipendra Misra, Akanksha Saran, Tengyang Xie, Alex Lamb, John Langford:
Towards Principled Representation Learning from Videos for Reinforcement Learning. CoRR abs/2403.13765 (2024) - [i33]Jonathan D. Chang, Wenhao Zhan, Owen Oertell, Kianté Brantley, Dipendra Misra, Jason D. Lee, Wen Sun:
Dataset Reset Policy Optimization for RLHF. CoRR abs/2404.08495 (2024) - [i32]Dipendra Misra, Aldo Pacchiano, Robert E. Schapire:
Provable Interactive Learning with Hindsight Instruction Feedback. CoRR abs/2404.09123 (2024) - [i31]Ge Gao, Alexey Taymanov, Eduardo Salinas, Paul Mineiro, Dipendra Misra:
Aligning LLM Agents by Learning Latent Preference from User Edits. CoRR abs/2404.15269 (2024) - [i30]Dylan J. Foster, Adam Block, Dipendra Misra:
Is Behavior Cloning All You Need? Understanding Horizon in Imitation Learning. CoRR abs/2407.15007 (2024) - 2023
- [i29]Anqi Li, Dipendra Misra, Andrey Kolobov, Ching-An Cheng:
Survival Instinct in Offline Reinforcement Learning. CoRR abs/2306.03286 (2023) - [i28]Jonathan D. Chang, Kianté Brantley, Rajkumar Ramamurthy, Dipendra Misra, Wen Sun:
Learning to Generate Better Than Your LLM. CoRR abs/2306.11816 (2023) - [i27]Ching-An Cheng, Andrey Kolobov, Dipendra Misra, Allen Nie, Adith Swaminathan:
LLF-Bench: Benchmark for Interactive Learning from Language Feedback. CoRR abs/2312.06853 (2023) - [i26]Pratyusha Sharma, Jordan T. Ash, Dipendra Misra:
The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction. CoRR abs/2312.13558 (2023) - 2022
- [i25]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 abs/2202.14037 (2022) - [i24]Yao Liu, Dipendra Misra, Miro Dudík, Robert E. Schapire:
Provably Sample-Efficient RL with Side Information about Latent Dynamics. CoRR abs/2205.14237 (2022) - [i23]Yonathan Efroni, Dylan J. Foster, Dipendra Misra, Akshay Krishnamurthy, John Langford:
Sample-Efficient Reinforcement Learning in the Presence of Exogenous Information. CoRR abs/2206.04282 (2022) - [i22]Alex Lamb, Riashat Islam
, Yonathan Efroni, Aniket Didolkar, Dipendra Misra, Dylan J. Foster, Lekan P. Molu, Rajan Chari, Akshay Krishnamurthy, John Langford:
Guaranteed Discovery of Controllable Latent States with Multi-Step Inverse Models. CoRR abs/2207.08229 (2022) - [i21]Andrew Bennett, Dipendra Misra, Nathan Kallus:
Provable Safe Reinforcement Learning with Binary Feedback. CoRR abs/2210.14492 (2022) - [i20]Riashat Islam
Agent-Controller Representations: Principled Offline RL with Rich Exogenous Information. CoRR abs/2211.00164 (2022) - [i19]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 abs/2211.07614 (2022) - 2021
- [i18]Khanh Nguyen, Dipendra Misra, Robert E. Schapire, Miroslav Dudík, Patrick Shafto:
Interactive Learning from Activity Description. CoRR abs/2102.07024 (2021) - [i17]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 abs/2105.10165 (2021) - [i16]Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Dipendra Misra:
Investigating the Role of Negatives in Contrastive Representation Learning. CoRR abs/2106.09943 (2021) - [i15]Yonathan Efroni, Dipendra Misra, Akshay Krishnamurthy, Alekh Agarwal, John Langford:
Provable RL with Exogenous Distractors via Multistep Inverse Dynamics. CoRR abs/2110.08847 (2021) - 2020
- [i14]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 abs/2010.03799 (2020) - 2019
- [i13]Kavosh Asadi, Dipendra Misra, Seungchan Kim, Michael L. Littman:
Combating the Compounding-Error Problem with a Multi-step Model. CoRR abs/1905.13320 (2019) - [i12]Dipendra Misra, Mikael Henaff, Akshay Krishnamurthy, John Langford:
Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning. CoRR abs/1911.05815 (2019) - 2018
- [i11]Claudia Yan, Dipendra Kumar Misra, Andrew Bennett, Aaron Walsman, Yonatan Bisk, Yoav Artzi:
CHALET: Cornell House Agent Learning Environment. CoRR abs/1801.07357 (2018) - [i10]Kavosh Asadi, Dipendra Misra, Michael L. Littman:
Lipschitz Continuity in Model-based Reinforcement Learning. CoRR abs/1804.07193 (2018) - [i9]Kavosh Asadi, Evan Cater, Dipendra Misra, Michael L. Littman:
Equivalence Between Wasserstein and Value-Aware Model-based Reinforcement Learning. CoRR abs/1806.01265 (2018) - [i8]Dipendra Kumar Misra, Andrew Bennett, Valts Blukis, Eyvind Niklasson, Max Shatkhin, Yoav Artzi:
Mapping Instructions to Actions in 3D Environments with Visual Goal Prediction. CoRR abs/1809.00786 (2018) - [i7]Dipendra Misra, Ming-Wei Chang, Xiaodong He, Wen-tau Yih:
Policy Shaping and Generalized Update Equations for Semantic Parsing from Denotations. CoRR abs/1809.01299 (2018) - [i6]Kavosh Asadi, Evan Cater, Dipendra Misra, Michael L. Littman:
Towards a Simple Approach to Multi-step Model-based Reinforcement Learning. CoRR abs/1811.00128 (2018) - [i5]Valts Blukis, Dipendra Kumar Misra, Ross A. Knepper, Yoav Artzi:
Mapping Navigation Instructions to Continuous Control Actions with Position-Visitation Prediction. CoRR abs/1811.04179 (2018) - [i4]Aaron Walsman, Yonatan Bisk, Saadia Gabriel, Dipendra Kumar Misra, Yoav Artzi, Yejin Choi, Dieter Fox:
Early Fusion for Goal Directed Robotic Vision. CoRR abs/1811.08824 (2018) - [i3]Howard Chen, Alane Suhr, Dipendra Kumar Misra, Noah Snavely, Yoav Artzi:
Touchdown: Natural Language Navigation and Spatial Reasoning in Visual Street Environments. CoRR abs/1811.12354 (2018) - 2017
- [i2]Dipendra Kumar Misra, John Langford, Yoav Artzi:
Mapping Instructions and Visual Observations to Actions with Reinforcement Learning. CoRR abs/1704.08795 (2017) - 2014
- [i1]Ashutosh Saxena, Ashesh Jain, Ozan Sener, Aditya Jami, Dipendra Kumar Misra, Hema Swetha Koppula:
RoboBrain: Large-Scale Knowledge Engine for Robots. CoRR abs/1412.0691 (2014)
Coauthor Index
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