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KDD
2012
ACM
212views Data Mining» more  KDD 2012»
11 years 10 months ago
Fast bregman divergence NMF using taylor expansion and coordinate descent
Non-negative matrix factorization (NMF) provides a lower rank approximation of a matrix. Due to nonnegativity imposed on the factors, it gives a latent structure that is often mor...
Liangda Li, Guy Lebanon, Haesun Park
ICA
2010
Springer
13 years 8 months ago
Common SpatioTemporal Pattern Analysis
In this work we present a method for the estimation of a rank-one pattern living in two heterogeneous spaces, when observed through a mixture in multiple observation sets. Using a ...
Ronald Phlypo, Nisrine Jrad, Bertrand Rivet, Marco...
SDM
2011
SIAM
414views Data Mining» more  SDM 2011»
12 years 10 months ago
Clustered low rank approximation of graphs in information science applications
In this paper we present a fast and accurate procedure called clustered low rank matrix approximation for massive graphs. The procedure involves a fast clustering of the graph and...
Berkant Savas, Inderjit S. Dhillon
SCIA
2009
Springer
305views Image Analysis» more  SCIA 2009»
14 years 2 months ago
A Convex Approach to Low Rank Matrix Approximation with Missing Data
Many computer vision problems can be formulated as low rank bilinear minimization problems. One reason for the success of these problems is that they can be efficiently solved usin...
Carl Olsson, Magnus Oskarsson
SIGIR
1995
ACM
13 years 11 months ago
Noise Reduction in a Statistical Approach to Text Categorization
This paper studies noise reduction for computational efficiency improvements in a statistical learning method for text categorization, the Linear Least Squares Fit (LLSF) mapping...
Yiming Yang