15 search results - page 3 / 3 » Leave-one-out Bounds for Support Vector Regression |
NIPS
2001
13 years 6 months ago
2001
Abstract--Kernel-based algorithms such as support vector machines have achieved considerable success in various problems in batch setting, where all of the training data is availab...
UAI
2003
13 years 6 months ago
2003
Many practitioners who use EM and related algorithms complain that they are sometimes slow. When does this happen, and what can be done about it? In this paper, we study the gener...
NIPS
2007
13 years 6 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 ...
JMLR
2010
13 years 3 months ago
2010
A wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and differen...
IJCNN
2007
IEEE
13 years 11 months ago
2007
IEEE
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...