Online learning algorithms

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal

76 Scopus Citations
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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)145-170
Journal / PublicationFoundations of Computational Mathematics
Volume6
Issue number2
Publication statusPublished - Jun 2006
Externally publishedYes

Abstract

In this paper, we study an online learning algorithm in Reproducing Kernel Hilbert Spaces (RKHSs) and general Hilbert spaces. We present a general form of the stochastic gradient method to minimize a quadratic potential function by an independent identically distributed (i.i.d.) sample sequence, and show a probabilistic upper bound for its convergence. © 2005 SFoCM.

Research Area(s)

  • Online learning, Regularization, Reproducing Kernel Hilbert Spaces, Stochastic approximation

Citation Format(s)

Online learning algorithms. / Smale, Steve; Yao, Yuan.

In: Foundations of Computational Mathematics, Vol. 6, No. 2, 06.2006, p. 145-170.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal