Home

About

Advanced Search

Browse by Discipline

Scientific Societies

E-print Alerts

Add E-prints

E-print Network
FAQHELPSITE MAPCONTACT US


  Advanced Search  

 
Incorporating Side Information in Probabilistic Matrix Factorization with Gaussian Processes
 

Summary: Incorporating Side Information in Probabilistic Matrix Factorization
with Gaussian Processes
Ryan Prescott Adams # George E. Dahl
Department of Computer Science
University of Toronto
Toronto, Canada
Iain Murray
School of Informatics
University of Edinburgh
Edinburgh, Scotland
Abstract
Probabilistic matrix factorization (PMF) is
a powerful method for modeling data associ­
ated with pairwise relationships, finding use
in collaborative filtering, computational bi­
ology, and document analysis, among other
areas. In many domains, there are additional
covariates that can assist in prediction. For
example, when modeling movie ratings, we
might know when the rating occurred, where

  

Source: Adams, Ryan Prescott - Department of Electrical and Computer Engineering, University of Toronto

 

Collections: Computer Technologies and Information Sciences