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» Optimal Solutions for Sparse Principal Component Analysis
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GECCO
2003
Springer
171views Optimization» more  GECCO 2003»
15 years 2 months ago
Genetic Algorithm Optimized Feature Transformation - A Comparison with Different Classifiers
When using a Genetic Algorithm (GA) to optimize the feature space of pattern classification problems, the performance improvement is not only determined by the data set used, but a...
Zhijian Huang, Min Pei, Erik D. Goodman, Yong Huan...
ICMCS
2006
IEEE
160views Multimedia» more  ICMCS 2006»
15 years 3 months ago
Selecting Kernel Eigenfaces for Face Recognition with One Training Sample Per Subject
It is well-known that supervised learning techniques such as linear discriminant analysis (LDA) often suffer from the so called small sample size problem when apply to solve face ...
Jie Wang, Konstantinos N. Plataniotis, Anastasios ...
ICPR
2010
IEEE
14 years 11 months ago
SemiCCA: Efficient Semi-Supervised Learning of Canonical Correlations
Canonical correlation analysis (CCA) is a powerful tool for analyzing multi-dimensional paired data. However, CCA tends to perform poorly when the number of paired samples is limit...
Akisato Kimura, Hirokazu Kameoka, Masashi Sugiyama...
ICPPW
2002
IEEE
15 years 2 months ago
A Statistical Approach for the Analysis of the Relation Between Low-Level Performance Information, the Code, and the Environment
This paper presents a methodology for aiding a scientific programmer to evaluate the performance of parallel programs on advanced architectures. It applies well-defined design o...
Nayda G. Santiago, Diane T. Rover, Domingo Rodr&ia...
EUROGRAPHICS
2010
Eurographics
15 years 6 months ago
Adding Depth to Cartoons Using Sparse Depth (In)equalities
This paper presents a novel interactive approach for adding depth information into hand-drawn cartoon images and animations. In comparison to previous depth assignment techniques ...
Daniel Sýkora, David Sedlacek, Sun Jinchao, John ...