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Poster
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Wed 17:00
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Characterizing the Exact Behaviors of Temporal Difference Learning Algorithms Using Markov Jump Linear System Theory
Bin Hu · Usman Syed
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Poster
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Tue 17:30
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Worst-Case Regret Bounds for Exploration via Randomized Value Functions
Daniel Russo
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Poster
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Tue 10:45
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Value Function in Frequency Domain and the Characteristic Value Iteration Algorithm
Amir-massoud Farahmand
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Poster
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Wed 17:00
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Large Scale Markov Decision Processes with Changing Rewards
Adrian Rivera Cardoso · He Wang · Huan Xu
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Poster
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Tue 10:45
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Limiting Extrapolation in Linear Approximate Value Iteration
Andrea Zanette · Alessandro Lazaric · Mykel J Kochenderfer · Emma Brunskill
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Poster
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Wed 10:45
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Finite-Time Performance Bounds and Adaptive Learning Rate Selection for Two Time-Scale Reinforcement Learning
Harsh Gupta · R. Srikant · Lei Ying
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Poster
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Tue 10:45
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Maximum Expected Hitting Cost of a Markov Decision Process and Informativeness of Rewards
Falcon Dai · Matthew Walter
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Poster
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Tue 17:30
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Exploration Bonus for Regret Minimization in Discrete and Continuous Average Reward MDPs
Jian QIAN · Ronan Fruit · Matteo Pirotta · Alessandro Lazaric
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Poster
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Tue 10:45
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Finite-Sample Analysis for SARSA with Linear Function Approximation
Shaofeng Zou · Tengyu Xu · Yingbin Liang
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Poster
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Wed 10:45
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A Regularized Approach to Sparse Optimal Policy in Reinforcement Learning
Wenhao Yang · Xiang Li · Zhihua Zhang
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Poster
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Tue 17:30
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Almost Horizon-Free Structure-Aware Best Policy Identification with a Generative Model
Andrea Zanette · Mykel J Kochenderfer · Emma Brunskill
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Poster
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Tue 17:30
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Explicit Planning for Efficient Exploration in Reinforcement Learning
Liangpeng Zhang · Ke Tang · Xin Yao
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