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SGDLibrary: A MATLAB library for stochastic gradient descent algorithms

27 October 2017
Hiroyuki Kasai
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Abstract

We consider the problem of finding the minimizer of a function f:Rd→Rf: \mathbb{R}^d \rightarrow \mathbb{R}f:Rd→R of the finite-sum form min⁡f(w)=1/n∑infi(w)\min f(w) = 1/n\sum_{i}^n f_i(w)minf(w)=1/n∑in​fi​(w). This problem has been studied intensively in recent years in the field of machine learning (ML). One promising approach for large-scale data is to use a stochastic optimization algorithm to solve the problem. SGDLibrary is a readable, flexible and extensible pure-MATLAB library of a collection of stochastic optimization algorithms. The purpose of the library is to provide researchers and implementers a comprehensive evaluation environment for the use of these algorithms on various ML problems.

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