220 search results - page 5 / 44 » Training linear SVMs in linear time |
NIPS
2001
13 years 8 months ago
2001
Guided by an initial idea of building a complex (non linear) decision surface with maximal local margin in input space, we give a possible geometrical intuition as to why K-Neares...
ECML
2006
Springer
13 years 9 months ago
2006
Springer
This paper presents a decomposition method for efficiently constructing 1-norm Support Vector Machines (SVMs). The decomposition algorithm introduced in this paper possesses many d...
SDM
2010
SIAM
13 years 8 months ago
2010
SIAM
The high computational cost of nonlinear support vector machines has limited their usability for large-scale problems. We propose two novel stochastic algorithms to tackle this pr...
BMCBI
2005
13 years 7 months ago
2005
Background: Baum-Welch training is an expectation-maximisation algorithm for training the emission and transition probabilities of hidden Markov models in a fully automated way. I...
JMLR
2010
13 years 2 months ago
2010
Kernel techniques have long been used in SVM to handle linearly inseparable problems by transforming data to a high dimensional space, but training and testing large data sets is ...