Multikernel Passive Stochastic Gradient Algorithms and Transfer Learning

This article develops a novel passive stochastic gradient algorithm. In passive stochastic approximation, the stochastic gradient algorithm does not have control over the location where noisy gradients of the cost function are evaluated. Classical passive stochastic gradient algorithms use a kernel...

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Vydané v:	IEEE transactions on automatic control Ročník 67; číslo 4; s. 1792 - 1805
Hlavní autori:	Krishnamurthy, Vikram, Yin, George
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.04.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms Approximation algorithms Bernstein von-Mises theorem Convergence Cost function Kernel Least mean squares Least mean squares algorithm Machine learning Monte Carlo methods Noise measurement Ordinary differential equations passive least mean squares (LMS) stochastic gradient algorithm stochastic sampling Transfer learning Variance analysis variance reduction weak convergence
ISSN:	0018-9286, 1558-2523
On-line prístup:	Získať plný text
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