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Guest editorial: special issue on reinforcement learning for real life

Machine learning, 2021-09, Vol.110 (9), p.2291-2293

2021

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Bandit Based Monte-Carlo Planning

Lecture notes in computer science, 2006, p.282-293

2006

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A modular analysis of adaptive (non-)convex optimization: Optimism, composite objectives, variance reduction, and variational bounds

Theoretical computer science, 2020-02, Vol.808, p.108-138

2020

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Exploration–exploitation tradeoff using variance estimates in multi-armed bandits

Theoretical computer science, 2009-04, Vol.410 (19), p.1876-1902

2009

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X-Armed Bandits

Journal of machine learning research, 2011-05, Vol.12, p.1655-1695

2011

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Learning near-optimal policies with Bellman-residual minimization based fitted policy iteration and a single sample path

Machine learning, 2008-04, Vol.71 (1), p.89-129

2008

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Stochastic Optimization in a Cumulative Prospect Theory Framework

IEEE transactions on automatic control, 2018-09, Vol.63 (9), p.2867-2882

2018

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Online Markov Decision Processes Under Bandit Feedback

IEEE transactions on automatic control, 2014-03, Vol.59 (3), p.676-691

2014

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Training parsers by inverse reinforcement learning

Machine learning, 2009-12, Vol.77 (2-3), p.303-337

2009

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A Linearly Relaxed Approximate Linear Program for Markov Decision Processes

IEEE transactions on automatic control, 2018-04, Vol.63 (4), p.1185-1191

2018

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Bounds and dynamics for empirical game theoretic analysis

Autonomous agents and multi-agent systems, 2020-04, Vol.34 (1), Article 7

2020

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MIXING TIME ESTIMATION IN REVERSIBLE MARKOV CHAINS FROM A SINGLE SAMPLE PATH

The Annals of applied probability, 2019-08, Vol.29 (4), p.2439-2480

2019

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Model selection in reinforcement learning

Machine learning, 2011-12, Vol.85 (3), p.299-332

2011

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Partial Monitoring-Classification, Regret Bounds, and Algorithms

Mathematics of operations research, 2014-11, Vol.39 (4), p.967-997

2014

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Optimistic MLE: A Generic Model-Based Algorithm for Partially Observable Sequential Decision Making

Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 2023, p.363-376

2023

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Algorithms for Reinforcement Learning

Synthesis lectures on artificial intelligence and machine learning, 2010, Vol.4 (1), p.1-103

Szepesvári, Csaba

2010

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Toward a classification of finite partial-monitoring games

Theoretical computer science, 2013-02, Vol.473, p.77-99

2013

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Alignment based kernel learning with a continuous set of base kernels

Machine learning, 2013-06, Vol.91 (3), p.305-324

2013

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Sequential Learning for Multi-Channel Wireless Network Monitoring With Channel Switching Costs

IEEE transactions on signal processing, 2014-11, Vol.62 (22), p.5919-5929

2014

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Convergence Results for Single-Step On-Policy Reinforcement-Learning Algorithms

Machine learning, 2000-03, Vol.38 (3), p.287-308

2000

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Improved Rates for the Stochastic Continuum-Armed Bandit Problem

Learning Theory, p.454-468

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Active learning in heteroscedastic noise

Theoretical computer science, 2010-06, Vol.411 (29), p.2712-2728

2010

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Regularized least-squares regression: Learning from a β - mixing sequence

Journal of statistical planning and inference, 2012-02, Vol.142 (2), p.493-505

2012

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Sequential learning for optimal monitoring of multi-channel wireless networks

2011 Proceedings IEEE INFOCOM, 2011, p.1152-1160

2011

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Universal parameter optimisation in games based on SPSA

Machine learning, 2006-06, Vol.63 (3), p.249-286

2006

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Guest editorial: special issue on reinforcement learning for real life

Bandit Based Monte-Carlo Planning

A modular analysis of adaptive (non-)convex optimization: Optimism, composite objectives, variance reduction, and variational bounds

Exploration–exploitation tradeoff using variance estimates in multi-armed bandits

X-Armed Bandits

Learning near-optimal policies with Bellman-residual minimization based fitted policy iteration and a single sample path

Stochastic Optimization in a Cumulative Prospect Theory Framework

Online Markov Decision Processes Under Bandit Feedback

Training parsers by inverse reinforcement learning

A Linearly Relaxed Approximate Linear Program for Markov Decision Processes

Bounds and dynamics for empirical game theoretic analysis

MIXING TIME ESTIMATION IN REVERSIBLE MARKOV CHAINS FROM A SINGLE SAMPLE PATH

Model selection in reinforcement learning

Partial Monitoring-Classification, Regret Bounds, and Algorithms

Optimistic MLE: A Generic Model-Based Algorithm for Partially Observable Sequential Decision Making

Algorithms for Reinforcement Learning

Toward a classification of finite partial-monitoring games

Alignment based kernel learning with a continuous set of base kernels

Sequential Learning for Multi-Channel Wireless Network Monitoring With Channel Switching Costs

Convergence Results for Single-Step On-Policy Reinforcement-Learning Algorithms

Improved Rates for the Stochastic Continuum-Armed Bandit Problem

Active learning in heteroscedastic noise

Regularized least-squares regression: Learning from a β - mixing sequence

Sequential learning for optimal monitoring of multi-channel wireless networks

Universal parameter optimisation in games based on SPSA

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