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03/28/2023
Function Approximation with Randomly Initialized Neural Networks for Approximate Model Reference Adaptive Control
Classical results in neural network approximation theory show how arbitr...
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03/21/2023
Non-Asymptotic Pointwise and Worst-Case Bounds for Classical Spectrum Estimators
Spectrum estimation is a fundamental methodology in the analysis of time...
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05/27/2022
Constrained Langevin Algorithms with L-mixing External Random Variables
Langevin algorithms are gradient descent methods augmented with additive...
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12/22/2020
Projected Stochastic Gradient Langevin Algorithms for Constrained Sampling and Non-Convex Learning
Langevin algorithms are gradient descent methods with additive noise. Th...
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09/06/2019
Trading-Off Static and Dynamic Regret in Online Least-Squares and Beyond
Recursive least-squares algorithms often use forgetting factors as a heu...
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06/18/2019
Simple Algorithms for Dueling Bandits
In this paper, we present simple algorithms for Dueling Bandits. We prov...
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01/23/2019
Online Adaptive Principal Component Analysis and Its extensions
We propose algorithms for online principal component analysis (PCA) and ...
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02/19/2018