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Bridging Exploration and General Function Approximation in Reinforcement Learning: Provably Efficient Kernel and Neural Value Iterations

Nov 09, 2020
Zhuoran Yang, Chi Jin, Zhaoran Wang, Mengdi Wang, Michael I. Jordan

* 76 pages. The short version of this work appears in NeurIPS 2020 

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Do Offline Metrics Predict Online Performance in Recommender Systems?

Nov 07, 2020
Karl Krauth, Sarah Dean, Alex Zhao, Wenshuo Guo, Mihaela Curmei, Benjamin Recht, Michael I. Jordan


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Efficient Methods for Structured Nonconvex-Nonconcave Min-Max Optimization

Oct 31, 2020
Jelena Diakonikolas, Constantinos Daskalakis, Michael I. Jordan


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Resource Allocation in Multi-armed Bandit Exploration: Overcoming Nonlinear Scaling with Adaptive Parallelism

Oct 31, 2020
Brijen Thananjeyan, Kirthevasan Kandasamy, Ion Stoica, Michael I. Jordan, Ken Goldberg, Joseph E. Gonzalez

* Preprint. Under review 

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Learning Strategies in Decentralized Matching Markets under Uncertain Preferences

Oct 29, 2020
Xiaowu Dai, Michael I. Jordan


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Uncertainty Sets for Image Classifiers using Conformal Prediction

Sep 29, 2020
Anastasios Angelopoulos, Stephen Bates, Jitendra Malik, Michael I. Jordan

* Codebase available at https://github.com/aangelopoulos/conformal_classification 

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Learning from eXtreme Bandit Feedback

Sep 27, 2020
Romain Lopez, Inderjit Dhillon, Michael I. Jordan


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Exploration in two-stage recommender systems

Sep 01, 2020
Jiri Hron, Karl Krauth, Michael I. Jordan, Niki Kilbertus

* Published at the REVEAL 2020 workshop (RecSys 2020) 

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ROOT-SGD: Sharp Nonasymptotics and Asymptotic Efficiency in a Single Algorithm

Aug 28, 2020
Chris Junchi Li, Wenlong Mou, Martin J. Wainwright, Michael I. Jordan


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On Localized Discrepancy for Domain Adaptation

Aug 14, 2020
Yuchen Zhang, Mingsheng Long, Jianmin Wang, Michael I. Jordan


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Transferable Calibration with Lower Bias and Variance in Domain Adaptation

Jul 16, 2020
Ximei Wang, Mingsheng Long, Jianmin Wang, Michael I. Jordan


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Optimal Robust Linear Regression in Nearly Linear Time

Jul 16, 2020
Yeshwanth Cherapanamjeri, Efe Aras, Nilesh Tripuraneni, Michael I. Jordan, Nicolas Flammarion, Peter L. Bartlett


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Manifold Learning via Manifold Deflation

Jul 07, 2020
Daniel Ting, Michael I. Jordan


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Accelerated Message Passing for Entropy-Regularized MAP Inference

Jul 01, 2020
Jonathan N. Lee, Aldo Pacchiano, Peter Bartlett, Michael I. Jordan


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Projection Robust Wasserstein Distance and Riemannian Optimization

Jun 28, 2020
Tianyi Lin, Chenyou Fan, Nhat Ho, Marco Cuturi, Michael I. Jordan

* The first two authors contributed equally 

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On Projection Robust Optimal Transport: Sample Complexity and Model Misspecification

Jun 26, 2020
Tianyi Lin, Zeyu Zheng, Elynn Y. Chen, Marco Cuturi, Michael I. Jordan

* Correct some typos; 46 Pages, 41 figures 

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On the Theory of Transfer Learning: The Importance of Task Diversity

Jun 20, 2020
Nilesh Tripuraneni, Michael I. Jordan, Chi Jin


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Active Learning for Nonlinear System Identification with Guarantees

Jun 18, 2020
Horia Mania, Michael I. Jordan, Benjamin Recht

* 29 pages 

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Instability, Computational Efficiency and Statistical Accuracy

May 22, 2020
Nhat Ho, Koulik Khamaru, Raaz Dwivedi, Martin J. Wainwright, Michael I. Jordan, Bin Yu

* First three authors contributed equally (listed in random order). 57 pages, 4 Figures 

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Lower bounds in multiple testing: A framework based on derandomized proxies

May 07, 2020
Max Rabinovich, Michael I. Jordan, Martin J. Wainwright


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Mechanism Design with Bandit Feedback

Apr 19, 2020
Kirthevasan Kandasamy, Joseph E. Gonzalez, Michael I. Jordan, Ion Stoica


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On Learning Rates and Schrödinger Operators

Apr 15, 2020
Bin Shi, Weijie J. Su, Michael I. Jordan

* 49 pages, 21 figures 

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On Dissipative Symplectic Integration with Applications to Gradient-Based Optimization

Apr 15, 2020
Guilherme França, Michael I. Jordan, René Vidal


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On Linear Stochastic Approximation: Fine-grained Polyak-Ruppert and Non-Asymptotic Concentration

Apr 09, 2020
Wenlong Mou, Chris Junchi Li, Martin J. Wainwright, Peter L. Bartlett, Michael I. Jordan


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Finite-Time Last-Iterate Convergence for Multi-Agent Learning in Games

Mar 18, 2020
Tianyi Lin, Zhengyuan Zhou, Panayotis Mertikopoulos, Michael I. Jordan

* Correct some typos 

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Revisiting Fixed Support Wasserstein Barycenter: Computational Hardness and Efficient Algorithms

Mar 18, 2020
Tianyi Lin, Nhat Ho, Xi Chen, Marco Cuturi, Michael I. Jordan

* Correct some typos 

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Is Temporal Difference Learning Optimal? An Instance-Dependent Analysis

Mar 16, 2020
Koulik Khamaru, Ashwin Pananjady, Feng Ruan, Martin J. Wainwright, Michael I. Jordan

* 38 pages, 3 figures 

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Post-Estimation Smoothing: A Simple Baseline for Learning with Side Information

Mar 12, 2020
Esther Rolf, Michael I. Jordan, Benjamin Recht

* To appear in AISTATS 2020 

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