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» Feature selection in a kernel space
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IJCAI
2007
15 years 4 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
142
Voted
SGAI
2004
Springer
15 years 8 months 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
139
Voted
ECCV
2010
Springer
15 years 5 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...
149
Voted
ICML
2010
IEEE
15 years 3 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
124
Voted
ICMCS
2005
IEEE
129views Multimedia» more  ICMCS 2005»
15 years 8 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...