145 search results - page 19 / 29 » On Constrained Sparse Matrix Factorization |
JMLR
2006
14 years 9 months ago
2006
In order to perform object recognition it is necessary to learn representations of the underlying components of images. Such components correspond to objects, object-parts, or fea...
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IJCNN
2008
IEEE
15 years 4 months ago
2008
IEEE
— We discuss sparse support vector machines (sparse SVMs) trained in the reduced empirical feature space. Namely, we select the linearly independent training data by the Cholesky...
ICANN
2007
Springer
15 years 4 months ago
2007
Springer
Abstract. In this paper we discuss sparse least squares support vector regressors (sparse LS SVRs) defined in the reduced empirical feature space, which is a subspace of mapped tr...
MM
2010
ACM
14 years 10 months ago
2010
ACM
The vast user-provided image tags on the popular photo sharing websites may greatly facilitate image retrieval and management. However, these tags are often imprecise and/or incom...
ICASSP
2010
IEEE
14 years 10 months ago
2010
IEEE
Co-clustering can be viewed as a two-way (bilinear) factorization of a large data matrix into dense/uniform and possibly overlapping submatrix factors (co-clusters). This combinat...