129 search results - page 7 / 26 » Matrix Decomposition Problem Is Complete for the Average Cas... |
FOCM
2011
13 years 2 months ago
2011
The matrix rank minimization problem has applications in many fields such as system identification, optimal control, low-dimensional embedding etc. As this problem is NP-hard in ...
KDD
2005
ACM
14 years 7 months ago
2005
ACM
Dyadic data matrices, such as co-occurrence matrix, rating matrix, and proximity matrix, arise frequently in various important applications. A fundamental problem in dyadic data a...
CORR
2004
Springer
13 years 7 months ago
2004
Springer
Non-negative matrix factorization (NMF) is a recently developed technique for finding parts-based, linear representations of non-negative data. Although it has successfully been a...
ICASSP
2009
IEEE
13 years 5 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...
SCIA
2009
Springer
14 years 1 months ago
2009
Springer
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...