171 search results - page 1 / 35 » Convex Sparse Matrix Factorizations |
CORR
2008
Springer
13 years 4 months ago
2008
Springer
We present a convex formulation of dictionary learning for sparse signal decomposition. Convexity is obtained by replacing the usual explicit upper bound on the dictionary size by...
EMMCVPR
2005
Springer
13 years 10 months ago
2005
Springer
Abstract. Reverse-convex programming (RCP) concerns global optimization of a specific class of non-convex optimization problems. We show that a recently proposed model for sparse ...
ICCV
2005
IEEE
14 years 6 months ago
2005
IEEE
Example-based learning of codes that statistically encode general image classes is of vital importance for computational vision. Recently, non-negative matrix factorization (NMF) ...
ISCAS
2008
IEEE
13 years 11 months ago
2008
IEEE
— Non-negative matrix factorization (NMF), i.e. V ≈ WH where both V, W and H are non-negative has become a widely used blind source separation technique due to its part based r...
SCIA
2009
Springer
13 years 11 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...