optimal value
Bias in Evaluation Processes: An Optimization-Based Model L. Elisa Celis Y ale University Amit Kumar IIT Delhi Anay Mehrotra Y ale University Nisheeth K. Vishnoi Y ale University
In these processes, an evaluator estimates an individual's value to an institution.
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Reinforcement Learning with Lookahead Information
In reinforcement learning (RL), agents sequentially interact with a changing environment, aiming to collect as much reward as possible.
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Flipping-based Policy for Chance-Constrained Markov Decision Processes
Safe reinforcement learning (RL) is a promising approach for many real-world decision-making problems where ensuring safety is a critical necessity.
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Counting the Optimal Solutions in Graphical Models
Neural Information Processing Systems http://nips.cc/
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Optimistic Distributionally Robust Optimization for Nonparametric Likelihood Approximation
Viet Anh Nguyen, Soroosh Shafieezadeh Abadeh, Man-Chung Yue, Daniel Kuhn, Wolfram Wiesemann
Neural Information Processing Systems http://nips.cc/
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Temporal Regularization for Markov Decision Process
Pierre Thodoroff, Audrey Durand, Joelle Pineau, Doina Precup
Yetinreinforcementlearning,duetothenatureofthe Bellman equation, there isanopportunity toalsoexploit temporal regularization based on smoothness in value estimates over trajectories. This paper explores a class of methods for temporal regularization.
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