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06/30/2023
Top-Two Thompson Sampling for Contextual Top-mc Selection Problems
We aim to efficiently allocate a fixed simulation budget to identify the...
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05/15/2023
Training Neural Networks without Backpropagation: A Deeper Dive into the Likelihood Ratio Method
Backpropagation (BP) is the most important gradient estimation method fo...
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05/12/2023
Quantile-Based Deep Reinforcement Learning using Two-Timescale Policy Gradient Algorithms
Classical reinforcement learning (RL) aims to optimize the expected cumu...
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05/06/2023
Efficient Learning for Selecting Top-m Context-Dependent Designs
We consider a simulation optimization problem for a context-dependent de...
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04/26/2022
An Efficient Dynamic Sampling Policy For Monte Carlo Tree Search
We consider the popular tree-based search strategy within the framework ...
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01/27/2022
Quantile-Based Policy Optimization for Reinforcement Learning
Classical reinforcement learning (RL) aims to optimize the expected cumu...
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01/27/2022
Efficient Distributed Learning in Stochastic Non-cooperative Games without Information Exchange
In this work, we study stochastic non-cooperative games, where only nois...
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11/30/2021
Asymptotically Optimal Sampling Policy for Selecting Top-m Alternatives
We consider selecting the top-m alternatives from a finite number of alt...
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02/06/2021
Noise Optimization for Artificial Neural Networks
Adding noises to artificial neural network(ANN) has been shown to be abl...
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12/10/2020
Efficient Learning for Clustering and Optimizing Context-Dependent Designs
We consider a simulation optimization problem for a context-dependent de...
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12/10/2020
Context-dependent Ranking and Selection under a Bayesian Framework
We consider a context-dependent ranking and selection problem. The best ...
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01/31/2019
Training Artificial Neural Networks by Generalized Likelihood Ratio Method: Exploring Brain-like Learning to Improve Adversarial Defensiveness
Recent work in deep learning has shown that the artificial neural networ...
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01/11/2019
Efficient Sampling for Selecting Important Nodes in Random Network
We consider the problem of selecting important nodes in a random network...
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10/07/2017