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05/18/2023
Bayesian Risk-Averse Q-Learning with Streaming Observations
We consider a robust reinforcement learning problem, where a learning ag...
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06/24/2022
Risk-averse Contextual Multi-armed Bandit Problem with Linear Payoffs
In this paper we consider the contextual multi-armed bandit problem for ...
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02/15/2022
Robust Multi-Objective Bayesian Optimization Under Input Noise
Bayesian optimization (BO) is a sample-efficient approach for tuning des...
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02/07/2022
Noise Regularizes Over-parameterized Rank One Matrix Recovery, Provably
We investigate the role of noise in optimization algorithms for learning...
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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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02/24/2021
Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization
Numerous empirical evidences have corroborated the importance of noise i...
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08/15/2020
Group Testing During the COVID-19 Pandemic: Optimal Group Size Selection and Prevalence Control
Group testing pools multiple samples together and performs tests on thes...
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07/11/2020
Solving Bayesian Risk Optimization via Nested Stochastic Gradient Estimation
In this paper, we aim to solve Bayesian Risk Optimization (BRO), which i...
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07/10/2020
Bayesian Optimization of Risk Measures
We consider Bayesian optimization of objective functions of the form ρ[ ...
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12/24/2019
Online Quantification of Input Model Uncertainty by Two-Layer Importance Sampling
Stochastic simulation has been widely used to analyze the performance of...
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09/10/2019
Towards Understanding the Importance of Shortcut Connections in Residual Networks
Residual Network (ResNet) is undoubtedly a milestone in deep learning. R...
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09/07/2019
Towards Understanding the Importance of Noise in Training Neural Networks
Numerous empirical evidence has corroborated that the noise plays a cruc...
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06/04/2018
Towards Understanding Acceleration Tradeoff between Momentum and Asynchrony in Nonconvex Stochastic Optimization
Asynchronous momentum stochastic gradient descent algorithms (Async-MSGD...
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02/14/2018
Toward Deeper Understanding of Nonconvex Stochastic Optimization with Momentum using Diffusion Approximations
Momentum Stochastic Gradient Descent (MSGD) algorithm has been widely ap...
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10/31/2017
