Efficient Matrix Completion with Gaussian Models

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.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2010
Accession Number
ADA540730

Entities

People

  • Flavien Léger
  • Guillermo Sapiro
  • Guoshen Yu

Organizations

  • University of Minnesota

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Computational Complexity
  • Covariance
  • Gaussian Distributions
  • Gaussian Processes
  • Image Processing
  • Inverse Problems
  • Mathematics
  • Models
  • Numbers
  • Probabilistic Models
  • Probability
  • Ratings
  • Square Roots
  • Standards
  • Statistical Algorithms
  • Test Sets

Fields of Study

  • Computer science

Readers

  • Computational Modeling and Simulation
  • Computer Vision.
  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)