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ICML
2010
IEEE
13 years 10 months ago
Learning Sparse SVM for Feature Selection on Very High Dimensional Datasets
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...
Mingkui Tan, Li Wang, Ivor W. Tsang
ICASSP
2011
IEEE
13 years 22 days ago
Compensation of extrinsic variability in speaker verification systems on simulated Skype and HF channel data
In this work we focus on speaker verification on channels of varying quality, namely Skype and high frequency (HF) radio. In our setup, we assume to have telephone recordings of ...
Korbinian Riedhammer, Tobias Bocklet, Elmar Nö...
CEC
2007
IEEE
14 years 1 months ago
Gene selection in cancer classification using PSO/SVM and GA/SVM hybrid algorithms
In this work we compare the use of a Particle Swarm Optimization (PSO) and a Genetic Algorithm (GA) (both augmented with Support Vector Machines SVM) for the classification of high...
Enrique Alba, José García-Nieto, Lae...
EMNLP
2009
13 years 6 months ago
Reverse Engineering of Tree Kernel Feature Spaces
We present a framework to extract the most important features (tree fragments) from a Tree Kernel (TK) space according to their importance in the target kernelbased machine, e.g. ...
Daniele Pighin, Alessandro Moschitti
ML
2011
ACM
308views Machine Learning» more  ML 2011»
13 years 3 months ago
Relational information gain
Abstract. Type Extension Trees (TET) have been recently introduced as an expressive representation language allowing to encode complex combinatorial features of relational entities...
Marco Lippi, Manfred Jaeger, Paolo Frasconi, Andre...