A Distributed HALS Algorithm for Euclidean Distance-Based Nonnegative Matrix Factorization

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Abstract

This paper proposes a distributed algorithm for multiple agents to perform the Nonnegative Matrix Factorization (NMF) based on the Euclidean distance. The matrix to be factorized is partitioned into multiple blocks, and each block is assigned to one of the agents forming a two-dimensional grid network. Each agent handles a small number of entries of the factor matrices corresponding to the assigned block, and updates their values by using information coming from the neighbors. It is shown that the proposed algorithm simulates the hierarchical alternating least squares method, which is well known as a fast algorithm for NMF based on the Euclidean distance, by making use of a finite-time distributed consensus algorithm.

Original languageEnglish
Title of host publication2019 IEEE Symposium Series on Computational Intelligence, SSCI 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1332-1337
Number of pages6
ISBN (Electronic)9781728124858
DOIs
Publication statusPublished - Dec 2019
Event2019 IEEE Symposium Series on Computational Intelligence, SSCI 2019 - Xiamen, China
Duration: Dec 6 2019Dec 9 2019

Publication series

Name2019 IEEE Symposium Series on Computational Intelligence, SSCI 2019

Conference

Conference2019 IEEE Symposium Series on Computational Intelligence, SSCI 2019
CountryChina
CityXiamen
Period12/6/1912/9/19

Keywords

  • distributed algorithm
  • finite-time consensus
  • hierarchical alternating least squares method
  • multiagent network
  • nonnegative matrix factorization

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Modelling and Simulation

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  • Cite this

    Domen, Y., Migita, T., & Takahashi, N. (2019). A Distributed HALS Algorithm for Euclidean Distance-Based Nonnegative Matrix Factorization. In 2019 IEEE Symposium Series on Computational Intelligence, SSCI 2019 (pp. 1332-1337). [9003158] (2019 IEEE Symposium Series on Computational Intelligence, SSCI 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SSCI44817.2019.9003158