545 search results - page 60 / 109 » Support Vector Regression Using Mahalanobis Kernels |
CIDM
2007
IEEE
14 years 27 days ago
2007
IEEE
Kernel methods are effective approaches to the modeling of structured objects in learning algorithms. Their major drawback is the typically high computational complexity of kernel ...
JMLR
2006
13 years 8 months ago
2006
This paper presents an online support vector machine (SVM) that uses the stochastic meta-descent (SMD) algorithm to adapt its step size automatically. We formulate the online lear...
BMCBI
2008
13 years 9 months ago
2008
In this paper we present preliminary results stemming from a novel application of Markov Models and Support Vector Machines to splice site classification of Intron-Exon and Exon-I...
ESANN
2008
13 years 10 months ago
2008
This paper presents a new approach for time series prediction using local dynamic modeling. The proposed method is composed of three blocks: a Time Delay Line that transforms the o...
ICML
2006
IEEE
14 years 9 months ago
2006
IEEE
The power and popularity of kernel methods stem in part from their ability to handle diverse forms of structured inputs, including vectors, graphs and strings. Recently, several m...