Convex Optimization for the Design of Learning Machines

Convex Optimization for the Design of Learning Machines

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by K. Pelckmans , J. A. K. Suykens , B. De Moor

BibTeX

@MISC{Pelckmans_convexoptimization,
    author = {K. Pelckmans and J. A. K. Suykens and B. De Moor},
    title = {Convex Optimization for the Design of Learning Machines},
    year = {}
}

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Abstract

Abstract. This paper reviews the recent surge of interest in convex optimization in a context of pattern recognition and machine learning. The main thesis of this paper is that the design of task-specific learning machines is aided substantially by using a convex optimization solver as a back-end to implement the task, liberating the designer from the concern of designing and analyzing an ad hoc algorithm. The aim of this paper is twofold: (i) it phrases the contributions of this ESANN 2007 special session in a broader context, and (ii) it provides a road-map to published resultsinthiscontext. 1

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