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CVPR
2001
IEEE
14 years 9 months ago
Learning Spatially Localized, Parts-Based Representation
In this paper, we propose a novel method, called local nonnegative matrix factorization (LNMF), for learning spatially localized, parts-based subspace representation of visual pat...
Stan Z. Li, XinWen Hou, HongJiang Zhang, QianSheng...
FOCM
2008
100views more  FOCM 2008»
13 years 7 months ago
Optimal Control and Geodesics on Quadratic Matrix Lie Groups
In this paper, we consider some matrix subgroups of the general linear group and in particular the special linear group that are defined by a quadratic matrix identity. The Lie al...
Anthony M. Bloch, Peter E. Crouch, Jerrold E. Mars...
EUROPAR
1997
Springer
13 years 11 months ago
A Relational Approach to the Compilation of Sparse Matrix Programs
Abstract. We present a relational algebra based framework for compiling e cient sparse matrix code from dense DO-ANY loops and a speci cation of the representation of the sparse ma...
Vladimir Kotlyar, Keshav Pingali, Paul Stodghill
ICDM
2008
IEEE
108views Data Mining» more  ICDM 2008»
14 years 2 months ago
Non-negative Matrix Factorization on Manifold
Recently Non-negative Matrix Factorization (NMF) has received a lot of attentions in information retrieval, computer vision and pattern recognition. NMF aims to find two non-nega...
Deng Cai, Xiaofei He, Xiaoyun Wu, Jiawei Han
LCPC
1998
Springer
13 years 11 months ago
HPF-2 Support for Dynamic Sparse Computations
There is a class of sparse matrix computations, such as direct solvers of systems of linear equations, that change the fill-in (nonzero entries) of the coefficient matrix, and invo...
Rafael Asenjo, Oscar G. Plata, Juan Touriño...