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02/27/2023
Global Algorithms for Mean-Variance Optimization in Markov Decision Processes
Dynamic optimization of mean and variance in Markov decision processes (...
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10/17/2022
Risk-Sensitive Markov Decision Processes with Long-Run CVaR Criterion
CVaR (Conditional Value at Risk) is a risk metric widely used in finance...
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09/14/2022
Distributionally Robust Offline Reinforcement Learning with Linear Function Approximation
Among the reasons hindering reinforcement learning (RL) applications to ...
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08/01/2022
Dominant Eigenvalue-Eigenvector Pair Estimation via Graph Infection
We present a novel method to estimate the dominant eigenvalue and eigenv...
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06/15/2022
Mean-Semivariance Policy Optimization via Risk-Averse Reinforcement Learning
Keeping risk under control is often more crucial than maximizing expecte...
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01/15/2022
A unified algorithm framework for mean-variance optimization in discounted Markov decision processes
This paper studies the risk-averse mean-variance optimization in infinit...
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06/07/2021
Average-Reward Reinforcement Learning with Trust Region Methods
Most of reinforcement learning algorithms optimize the discounted criter...
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03/06/2021
Zero-Sum Semi-Markov Games with State-Action-Dependent Discount Factors
Semi-Markov model is one of the most general models for stochastic dynam...
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03/06/2021
Zero-sum risk-sensitive continuous-time stochastic games with unbounded payoff and transition rates and Borel spaces
We study a finite-horizon two-person zero-sum risk-sensitive stochastic ...
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08/09/2020
Risk-Sensitive Markov Decision Processes with Combined Metrics of Mean and Variance
This paper investigates the optimization problem of an infinite stage di...
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06/25/2020
SOAC: The Soft Option Actor-Critic Architecture
The option framework has shown great promise by automatically extracting...
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06/20/2020
Embedding-based Retrieval in Facebook Search
Search in social networks such as Facebook poses different challenges th...
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06/05/2020
Wasserstein Distance guided Adversarial Imitation Learning with Reward Shape Exploration
The generative adversarial imitation learning (GAIL) has provided an adv...
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04/30/2020
Distributional Soft Actor Critic for Risk Sensitive Learning
Most of reinforcement learning (RL) algorithms aim at maximizing the exp...
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03/17/2020
Multi-action Offline Policy Learning with Bayesian Optimization
We study an offline multi-action policy learning algorithm based on doub...
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07/24/2019
An Overview for Markov Decision Processes in Queues and Networks
Markov decision processes (MDPs) in queues and networks have been an int...
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01/05/2019
Optimal Asynchronous Dynamic Policies in Energy-Efficient Data Centers
In this paper, we use a Markov decision process to find optimal asynchro...
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06/11/2017
