94 search results - page 1 / 19 » Variable Sparsity Kernel Learning |
138
Voted
JMLR
2011
14 years 10 months ago
2011
This paper1 presents novel algorithms and applications for a particular class of mixed-norm regularization based Multiple Kernel Learning (MKL) formulations. The formulations assu...
102
Voted
NIPS
2007
15 years 5 months ago
2007
Hierarchical penalization is a generic framework for incorporating prior information in the fitting of statistical models, when the explicative variables are organized in a hiera...
131
Voted
NIPS
2000
15 years 4 months ago
2000
We present an improvement of Noviko 's perceptron convergence theorem. Reinterpreting this mistakebound as a margindependent sparsity guarantee allows us to give a PAC{style ...
158
Voted
ICML
2010
IEEE
15 years 4 months ago
2010
IEEE
A sparse representation of Support Vector Machines (SVMs) with respect to input features is desirable for many applications. In this paper, by introducing a 0-1 control variable t...
148
Voted
ICIP
2010
IEEE
15 years 1 months ago
2010
IEEE
We propose a motion deblurring algorithm that exploits sparsity constraints of image patches using one single frame. In our formulation, each image patch is encoded with sparse co...