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ICML
2005
IEEE
15 years 11 months ago
Predictive low-rank decomposition for kernel methods
Low-rank matrix decompositions are essential tools in the application of kernel methods to large-scale learning problems. These decompositions have generally been treated as black...
Francis R. Bach, Michael I. Jordan
KDD
2012
ACM
212views Data Mining» more  KDD 2012»
13 years 1 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
112
Voted
ICC
2011
IEEE
217views Communications» more  ICC 2011»
13 years 10 months ago
Controlling LDPC Absorbing Sets via the Null Space of the Cycle Consistency Matrix
— This paper focuses on controlling absorbing sets for a class of regular LDPC codes, known as separable, circulantbased (SCB) codes. For a specified circulant matrix, SCB codes...
Jiadong Wang, Lara Dolecek, Richard D. Wesel
IVCNZ
1998
15 years 6 days ago
On Estimation of Fundamental Matrix in Computational Stereo
We address the problem of estimating a fundamental matrix from a given set of corresponding pixels in two perspective images of a 3D scene that form a stereopair. The 3x3 fundamen...
Yuping Li, Georgy L. Gimel'farb
SIAMSC
2008
167views more  SIAMSC 2008»
14 years 10 months ago
Low-Dimensional Polytope Approximation and Its Applications to Nonnegative Matrix Factorization
In this study, nonnegative matrix factorization is recast as the problem of approximating a polytope on the probability simplex by another polytope with fewer facets. Working on th...
Moody T. Chu, Matthew M. Lin