Sgdlibrary: A matlab library for stochastic optimization algorithms

Hiroyuki Kasai*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

We consider the problem of finding the minimizer of a function f : Rd → R of the finite-sum form min f(w) = 1/nn i 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.

Original languageEnglish
Pages (from-to)1-5
Number of pages5
JournalJournal of Machine Learning Research
Volume18
Publication statusPublished - 2018 Apr 1
Externally publishedYes

Keywords

  • Finite-sum minimization problem
  • Large-scale optimization problem
  • Stochastic gradient
  • Stochastic optimization

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Statistics and Probability
  • Artificial Intelligence

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