18 search results - page 1 / 4 » Sparse Kernel SVMs via Cutting-Plane Training |
PKDD
2009
Springer
13 years 11 months ago
2009
Springer
We explore an algorithm for training SVMs with Kernels that can represent the learned rule using arbitrary basis vectors, not just the support vectors (SVs) from the training set. ...
KDD
2006
ACM
14 years 4 months ago
2006
ACM
Linear Support Vector Machines (SVMs) have become one of the most prominent machine learning techniques for highdimensional sparse data commonly encountered in applications like t...
KDD
2008
ACM
14 years 4 months ago
2008
ACM
Discriminative training for structured outputs has found increasing applications in areas such as natural language processing, bioinformatics, information retrieval, and computer ...
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...
NIPS
1998
13 years 5 months ago
1998
Training a Support Vector Machine (SVM) requires the solution of a very large quadratic programming (QP) problem. This paper proposes an algorithm for training SVMs: Sequential Mi...