SGDLibrary: A MATLAB library for stochastic optimization algorithms
Hiroyuki Kasai; 18(215):1−5, 2018.
Abstract
We consider the problem of finding the minimizer of a function f:Rd→R of the finite-sum form min. 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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