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Cautiously Optimistic Policy Optimization and Exploration with Linear Function Approximation


Mar 24, 2021
Andrea Zanette, Ching-An Cheng, Alekh Agarwal

* Initial submission 

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Provably Correct Optimization and Exploration with Non-linear Policies


Mar 22, 2021
Fei Feng, Wotao Yin, Alekh Agarwal, Lin F. Yang


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Towards a Dimension-Free Understanding of Adaptive Linear Control


Mar 19, 2021
Juan C. Perdomo, Max Simchowitz, Alekh Agarwal, Peter Bartlett


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Model-free Representation Learning and Exploration in Low-rank MDPs


Feb 14, 2021
Aditya Modi, Jinglin Chen, Akshay Krishnamurthy, Nan Jiang, Alekh Agarwal


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PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient Learning


Aug 13, 2020
Alekh Agarwal, Mikael Henaff, Sham Kakade, Wen Sun


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Provably Good Batch Reinforcement Learning Without Great Exploration


Jul 22, 2020
Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill

* 36 pages, 7 figures 

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Policy Improvement from Multiple Experts


Jul 01, 2020
Ching-An Cheng, Andrey Kolobov, Alekh Agarwal


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Safe Reinforcement Learning via Curriculum Induction


Jun 22, 2020
Matteo Turchetta, Andrey Kolobov, Shital Shah, Andreas Krause, Alekh Agarwal


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Optimizing Interactive Systems via Data-Driven Objectives


Jun 19, 2020
Ziming Li, Julia Kiseleva, Alekh Agarwal, Maarten de Rijke, Ryen W. White

* 30 pages, 12 figures. arXiv admin note: text overlap with arXiv:1802.06306 

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FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs


Jun 18, 2020
Alekh Agarwal, Sham Kakade, Akshay Krishnamurthy, Wen Sun


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Reparameterized Variational Divergence Minimization for Stable Imitation


Jun 18, 2020
Dilip Arumugam, Debadeepta Dey, Alekh Agarwal, Asli Celikyilmaz, Elnaz Nouri, Bill Dolan


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Federated Residual Learning


Mar 28, 2020
Alekh Agarwal, John Langford, Chen-Yu Wei


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Taking a hint: How to leverage loss predictors in contextual bandits?


Mar 04, 2020
Chen-Yu Wei, Haipeng Luo, Alekh Agarwal


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Optimality and Approximation with Policy Gradient Methods in Markov Decision Processes


Aug 29, 2019
Alekh Agarwal, Sham M. Kakade, Jason D. Lee, Gaurav Mahajan

* Additional references and discussion of prior work 

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On the Optimality of Sparse Model-Based Planning for Markov Decision Processes


Jul 04, 2019
Alekh Agarwal, Sham Kakade, Lin F. Yang


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Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting


Jun 23, 2019
Aditya Grover, Jiaming Song, Alekh Agarwal, Kenneth Tran, Ashish Kapoor, Eric Horvitz, Stefano Ermon


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Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds


Jun 09, 2019
Jordan T. Ash, Chicheng Zhang, Akshay Krishnamurthy, John Langford, Alekh Agarwal


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Fair Regression: Quantitative Definitions and Reduction-based Algorithms


May 30, 2019
Alekh Agarwal, Miroslav Dudík, Zhiwei Steven Wu


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Metareasoning in Modular Software Systems: On-the-Fly Configuration using Reinforcement Learning with Rich Contextual Representations


May 12, 2019
Aditya Modi, Debadeepta Dey, Alekh Agarwal, Adith Swaminathan, Besmira Nushi, Sean Andrist, Eric Horvitz

* 12 pages, 7 figures, 2 tables 

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Off-Policy Policy Gradient with State Distribution Correction


Apr 17, 2019
Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill


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Provably efficient RL with Rich Observations via Latent State Decoding


Jan 25, 2019
Simon S. Du, Akshay Krishnamurthy, Nan Jiang, Alekh Agarwal, Miroslav Dudík, John Langford


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Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback


Jan 02, 2019
Chicheng Zhang, Alekh Agarwal, Hal Daumé III, John Langford, Sahand N Negahban

* 43 pages, 21 figures 

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Model-Based Reinforcement Learning in Contextual Decision Processes


Nov 21, 2018
Wen Sun, Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal, John Langford

* 30 

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On Oracle-Efficient PAC RL with Rich Observations


Oct 31, 2018
Christoph Dann, Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal, John Langford, Robert E. Schapire

* appearing at NIPS 18; full paper including appendix 

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A Reductions Approach to Fair Classification


Jul 16, 2018
Alekh Agarwal, Alina Beygelzimer, Miroslav Dudík, John Langford, Hanna Wallach


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Hierarchical Imitation and Reinforcement Learning


Jun 09, 2018
Hoang M. Le, Nan Jiang, Alekh Agarwal, Miroslav Dudík, Yisong Yue, Hal Daumé III

* Proceedings of the 35th International Conference on Machine Learning (ICML 2018) 

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