Efficient matrix completion with Gaussian models

Flavien Léger, Guoshen Yu, Guillermo Sapiro

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

A general framework based on Gaussian models and a MAPEM algorithm is introduced in this paper for solving matrix/ table completion problems. The numerical experiments with the standard and challenging movie ratings data show that the proposed approach, based on probably one of the simplest probabilistic models, leads to the results in the same ballpark as the state-of-the-art, at a lower computational cost.

Original languageEnglish (US)
Title of host publication2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Proceedings
Pages1113-1116
Number of pages4
DOIs
StatePublished - 2011
Externally publishedYes
Event36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Prague, Czech Republic
Duration: May 22 2011May 27 2011

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011
Country/TerritoryCzech Republic
CityPrague
Period5/22/115/27/11

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Keywords

  • collaborative filtering
  • EM algorithm
  • Gaussian mixture models
  • inverse problems
  • MAP estimation
  • Matrix completion

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