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» Feature selection in a kernel space
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IJCAI
2007
13 years 9 months ago
Parametric Kernels for Sequence Data Analysis
A key challenge in applying kernel-based methods for discriminative learning is to identify a suitable kernel given a problem domain. Many methods instead transform the input data...
Young-In Shin, Donald S. Fussell
SGAI
2004
Springer
14 years 27 days ago
Interactive Selection of Visual Features through Reinforcement Learning
We introduce a new class of Reinforcement Learning algorithms designed to operate in perceptual spaces containing images. They work by classifying the percepts using a computer vi...
Sébastien Jodogne, Justus H. Piater
ECCV
2010
Springer
13 years 10 months ago
Clustering Complex Data with Group-Dependent Feature Selection
Abstract. We describe a clustering approach with the emphasis on detecting coherent structures in a complex dataset, and illustrate its effectiveness with computer vision applicat...
ICML
2010
IEEE
13 years 8 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
ICMCS
2005
IEEE
129views Multimedia» more  ICMCS 2005»
14 years 1 months ago
Feature Selection and Stacking for Robust Discrimination of Speech, Monophonic Singing, and Polyphonic Music
In this work we strive to find an optimal set of acoustic features for the discrimination of speech, monophonic singing, and polyphonic music to robustly segment acoustic media st...
Björn Schuller, Brüning J. B. Schmitt, D...