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AAAI
2006
15 years 1 months ago
A Simple and Effective Method for Incorporating Advice into Kernel Methods
We propose a simple mechanism for incorporating advice (prior knowledge), in the form of simple rules, into support-vector methods for both classification and regression. Our appr...
Richard Maclin, Jude W. Shavlik, Trevor Walker, Li...
BMCBI
2008
93views more  BMCBI 2008»
14 years 11 months ago
Hybrid MM/SVM structural sensors for stochastic sequential data
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...
Brian Roux, Stephen Winters-Hilt
CAIP
2009
Springer
210views Image Analysis» more  CAIP 2009»
15 years 3 months ago
Shape Classification Using a Flexible Graph Kernel
The medial axis being an homotopic transformation, the skeleton of a 2D shape corresponds to a planar graph having one face for each hole of the shape and one node for each junctio...
François-Xavier Dupé, Luc Brun
ICML
2003
IEEE
16 years 14 days ago
Kernel PLS-SVC for Linear and Nonlinear Classification
A new method for classification is proposed. This is based on kernel orthonormalized partial least squares (PLS) dimensionality reduction of the original data space followed by a ...
Roman Rosipal, Leonard J. Trejo, Bryan Matthews
ML
2010
ACM
181views Machine Learning» more  ML 2010»
14 years 10 months ago
Decomposing the tensor kernel support vector machine for neuroscience data with structured labels
Abstract The tensor kernel has been used across the machine learning literature for a number of purposes and applications, due to its ability to incorporate samples from multiple s...
David R. Hardoon, John Shawe-Taylor