137 search results - page 2 / 28 » A Direct Method for Building Sparse Kernel Learning Algorith... |
JMLR
2002
13 years 4 months ago
2002
We present some greedy learning algorithms for building sparse nonlinear regression and classification models from observational data using Mercer kernels. Our objective is to dev...
ICML
2010
IEEE
13 years 5 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...
ICASSP
2011
IEEE
12 years 8 months ago
2011
IEEE
In this work a new online learning algorithm that uses automatic relevance determination (ARD) is proposed for fast adaptive nonlinear filtering. A sequential decision rule for i...
ICML
2008
IEEE
14 years 5 months ago
2008
IEEE
The Support Vector Machine (SVM) is an acknowledged powerful tool for building classifiers, but it lacks flexibility, in the sense that the kernel is chosen prior to learning. Mul...
TNN
2010
12 years 11 months ago
2010
Abstract--Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subse...