SGDLibrary: A MATLAB library for stochastic gradient descent algorithms
Mathematical Software
2018-07-04 v2 Computation
Machine Learning
Abstract
We consider the problem of finding the minimizer of a function of the finite-sum form . 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.
Keywords
Cite
@article{arxiv.1710.10951,
title = {SGDLibrary: A MATLAB library for stochastic gradient descent algorithms},
author = {Hiroyuki Kasai},
journal= {arXiv preprint arXiv:1710.10951},
year = {2018}
}