Sciweavers

13 search results - page 1 / 3
» Learning Non-Negative Sparse Image Codes by Convex Programmi...
Sort
View
ICCV
2005
IEEE
15 years 20 days ago
Learning Non-Negative Sparse Image Codes by Convex Programming
Example-based learning of codes that statistically encode general image classes is of vital importance for computational vision. Recently, non-negative matrix factorization (NMF) ...
Christoph Schnörr, Matthias Heiler
ICIP
2008
IEEE
15 years 14 days ago
Face hallucination VIA sparse coding
In this paper, we address the problem of hallucinating a high resolution face given a low resolution input face. The problem is approached through sparse coding. To exploit the fa...
Jianchao Yang, Hao Tang, Yi Ma, Thomas S. Huang
ECCV
2006
Springer
15 years 19 days ago
Controlling Sparseness in Non-negative Tensor Factorization
Non-negative tensor factorization (NTF) has recently been proposed as sparse and efficient image representation (Welling and Weber, Patt. Rec. Let., 2001). Until now, sparsity of t...
Matthias Heiler, Christoph Schnörr
EMMCVPR
2005
Springer
14 years 4 months ago
Reverse-Convex Programming for Sparse Image Codes
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 ...
Matthias Heiler, Christoph Schnörr
JMLR
2010
195views more  JMLR 2010»
13 years 9 months ago
Online Learning for Matrix Factorization and Sparse Coding
Sparse coding—that is, modelling data vectors as sparse linear combinations of basis elements—is widely used in machine learning, neuroscience, signal processing, and statisti...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...