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CVPR
2005
IEEE
14 years 7 months ago
2005
IEEE
Matrix factorization has many applications in computer vision. Singular Value Decomposition (SVD) is the standard algorithm for factorization. When there are outliers and missing ...
CVPR
2010
IEEE
13 years 3 months ago
2010
IEEE
The calculation of a low-rank approximation of a matrix is a fundamental operation in many computer vision applications. The workhorse of this class of problems has long been the ...
ICASSP
2009
IEEE
13 years 3 months ago
2009
IEEE
Nonnegative matrix factorization (NMF) is a widely-used method for low-rank approximation (LRA) of a nonnegative matrix (matrix with only nonnegative entries), where nonnegativity...
SLSFS
2005
Springer
13 years 10 months ago
2005
Springer
Abstract. Matrix factorization is a fundamental building block in many computer vision and machine learning algorithms. In this work we focus on the problem of ”structure from mo...
ICPPW
2002
IEEE
13 years 10 months ago
2002
IEEE
The effectiveness of the memory hierarchy is critical for the performance of current processors. The performance of the memory hierarchy can be improved by means of program transf...