65 search results - page 1 / 13 » Convergence of a Generalized Gradient Selection Approach for... |
ALT
2004
Springer
14 years 1 months ago
2004
Springer
The decomposition method is currently one of the major methods for solving the convex quadratic optimization problems being associated with support vector machines. For a special c...
CORR
2012
Springer
12 years 9 days ago
2012
Springer
We study the problem of learning high dimensional regression models regularized by a structured-sparsity-inducing penalty that encodes prior structural information on either input...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
The advances in kernel-based learning necessitate the study on solving a large-scale non-sparse positive definite linear system. To provide a deterministic approach, recent resear...
ICDM
2009
IEEE
13 years 11 months ago
2009
IEEE
—Many real world learning problems can be recast as multi-task learning problems which utilize correlations among different tasks to obtain better generalization performance than...
COLT
2005
Springer
13 years 10 months ago
2005
Springer
We present a general decomposition algorithm that is uniformly applicable to every (suitably normalized) instance of Convex Quadratic Optimization and efficiently approaches an o...