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PerSim: Data-Efficient Offline Reinforcement Learning with Heterogeneous Agents via Personalized Simulators


Mar 17, 2021
Anish Agarwal, Abdullah Alomar, Varkey Alumootil, Devavrat Shah, Dennis Shen, Zhi Xu, Cindy Yang


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Approximating the Log-Partition Function


Feb 19, 2021
Romain Cosson, Devavrat Shah


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Regret, stability, and fairness in matching markets with bandit learners


Feb 11, 2021
Sarah H. Cen, Devavrat Shah

* 37 pages 

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Gradient-Based Empirical Risk Minimization using Local Polynomial Regression


Nov 04, 2020
Ali Jadbabaie, Anuran Makur, Devavrat Shah

* 34 pages 

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On Learning Continuous Pairwise Markov Random Fields


Oct 28, 2020
Abhin Shah, Devavrat Shah, Gregory W. Wornell


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On Principal Component Regression in a High-Dimensional Error-in-Variables Setting


Oct 27, 2020
Anish Agarwal, Devavrat Shah, Dennis Shen


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On Multivariate Singular Spectrum Analysis


Jun 24, 2020
Anish Agarwal, Abdullah Alomar, Devavrat Shah


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Estimation of Skill Distributions


Jun 15, 2020
Ali Jadbabaie, Anuran Makur, Devavrat Shah

* 37 pages, 1 figure 

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Synthetic Interventions


Jun 13, 2020
Anish Agarwal, Abdullah Alomar, Romain Cosson, Devavrat Shah, Dennis Shen


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Sample Efficient Reinforcement Learning via Low-Rank Matrix Estimation


Jun 11, 2020
Devavrat Shah, Dogyoon Song, Zhi Xu, Yuzhe Yang


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Stable Reinforcement Learning with Unbounded State Space


Jun 08, 2020
Devavrat Shah, Qiaomin Xie, Zhi Xu


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Two Burning Questions on COVID-19: Did shutting down the economy help? Can we (partially) reopen the economy without risking the second wave?


May 10, 2020
Anish Agarwal, Abdullah Alomar, Arnab Sarker, Devavrat Shah, Dennis Shen, Cindy Yang


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On Reinforcement Learning for Turn-based Zero-sum Markov Games


Feb 25, 2020
Devavrat Shah, Varun Somani, Qiaomin Xie, Zhi Xu


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Short and Wide Network Paths


Nov 01, 2019
Lavanya Marla, Lav R. Varshney, Devavrat Shah, Nirmal A. Prakash, Michael E. Gale


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Iterative Collaborative Filtering for Sparse Noisy Tensor Estimation


Aug 03, 2019
Devavrat Shah, Christina Lee Yu


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On Reinforcement Learning Using Monte Carlo Tree Search with Supervised Learning: Non-Asymptotic Analysis


Apr 12, 2019
Devavrat Shah, Qiaomin Xie, Zhi Xu


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Time Series Predict DB


Mar 17, 2019
Abdullah Alomar, Muhammad J. Amjad, Robert Lindland, Devavrat Shah


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Model Agnostic High-Dimensional Error-in-Variable Regression


Mar 12, 2019
Anish Agarwal, Devavrat Shah, Dennis Shen, Dogyoon Song

* 51 pages 

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Learning Mixture Model with Missing Values and its Application to Rankings


Dec 31, 2018
Devavrat Shah, Dogyoon Song

* 47 pages, 4 figures 

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Q-learning with Nearest Neighbors


Oct 23, 2018
Devavrat Shah, Qiaomin Xie

* Accepted to NIPS 2018 

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Regret vs. Bandwidth Trade-off for Recommendation Systems


Oct 15, 2018
Linqi Song, Christina Fragouli, Devavrat Shah


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Time Series Analysis via Matrix Estimation


Aug 24, 2018
Anish Agarwal, Muhammad Jehangir Amjad, Devavrat Shah, Dennis Shen


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Leaders, Followers, and Community Detectio


Jun 29, 2018
Dhruv Parthasarathy, Devavrat Shah, Tauhid Zaman

* 11 pages, 6 figures 

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Reducing Crowdsourcing to Graphon Estimation, Statistically


Feb 21, 2018
Devavrat Shah, Christina Lee Yu


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Robust Synthetic Control


Nov 18, 2017
Muhammad Jehangir Amjad, Devavrat Shah, Dennis Shen


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Regret Guarantees for Item-Item Collaborative Filtering


Jan 08, 2016
Guy Bresler, Devavrat Shah, Luis F. Voloch


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Rank Centrality: Ranking from Pair-wise Comparisons


Nov 12, 2015
Sahand Negahban, Sewoong Oh, Devavrat Shah

* 45 pages, 3 figures 

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