267 search results - page 3 / 54 » Convex optimization for the design of learning machines |
ALT
2004
Springer
14 years 4 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...
ICASSP
2008
IEEE
14 years 1 months ago
2008
IEEE
The performance of a kernel-based learning algorithm depends very much on the choice of the kernel. Recently, much attention has been paid to the problem of learning the kernel it...
IJON
2007
13 years 7 months ago
2007
Unlike the conventional neural network theories and implementations, Huang et al. [Universal approximation using incremental constructive feedforward networks with random hidden n...
NIPS
2007
13 years 8 months ago
2007
We present a globally convergent method for regularized risk minimization problems. Our method applies to Support Vector estimation, regression, Gaussian Processes, and any other ...
COLT
2010
Springer
13 years 5 months ago
2010
Springer
Bandit convex optimization is a special case of online convex optimization with partial information. In this setting, a player attempts to minimize a sequence of adversarially gen...