112 search results - page 2 / 23 » Kernel-based online machine learning and support vector redu... |
PKDD
2010
Springer
13 years 3 months ago
2010
Springer
Prior knowledge, in the form of simple advice rules, can greatly speed up convergence in learning algorithms. Online learning methods predict the label of the current point and the...
ICML
2006
IEEE
14 years 5 months ago
2006
IEEE
In machine learning problems with tens of thousands of features and only dozens or hundreds of independent training examples, dimensionality reduction is essential for good learni...
ICCV
2007
IEEE
13 years 11 months ago
2007
IEEE
This paper treats tracking as a foreground/background classification problem and proposes an online semisupervised learning framework. Initialized with a small number of labeled ...
NIPS
2000
13 years 6 months ago
2000
An on-line recursive algorithm for training support vector machines, one vector at a time, is presented. Adiabatic increments retain the KuhnTucker conditions on all previously se...
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
In this paper we describe a new method to reduce the complexity of support vector machines by reducing the number of necessary support vectors included in their solutions. The red...