52 search results - page 8 / 11 » Learning Nonlinear Overcomplete Representations for Efficien... |
ICCV
2005
IEEE
16 years 7 hour 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) ...
CVPR
2007
IEEE
16 years 3 days ago
2007
IEEE
We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...
BMVC
2010
14 years 8 months ago
2010
Kernel methods yield state-of-the-art performance in certain applications such as image classification and object detection. However, large scale problems require machine learning...
CORR
2002
Springer
14 years 10 months ago
2002
Springer
Abstract. Non-negative sparse coding is a method for decomposing multivariate data into non-negative sparse components. In this paper we briefly describe the motivation behind this...
GRC
2008
IEEE
14 years 11 months ago
2008
IEEE
Manifold learning can discover the structure of high dimensional data and provides understanding of multidimensional patterns by preserving the local geometric characteristics. Ho...