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GECCO
2006
Springer
162views Optimization» more  GECCO 2006»
15 years 3 months ago
Evolutionary learning with kernels: a generic solution for large margin problems
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...
Ingo Mierswa
ICPR
2006
IEEE
16 years 28 days ago
Weakly Supervised Learning on Pre-image Problem in Kernel Methods
This paper presents a novel alternative approach, namely weakly supervised learning (WSL), to learn the pre-image of a feature vector in the feature space induced by a kernel. It ...
Weishi Zheng, Jian-Huang Lai, Pong Chi Yuen
IJCNN
2008
IEEE
15 years 6 months ago
Feature selection based on kernel discriminant analysis for multi-class problems
— We propose a feature selection criterion based on kernel discriminant analysis (KDA) for an -class problem, which finds eigenvectors on which the projected class data are loca...
Tsuneyoshi Ishii, Shigeo Abe
NECO
1998
151views more  NECO 1998»
14 years 11 months ago
Nonlinear Component Analysis as a Kernel Eigenvalue Problem
We describe a new method for performing a nonlinear form of Principal Component Analysis. By the use of integral operator kernel functions, we can e ciently compute principal comp...
Bernhard Schölkopf, Alex J. Smola, Klaus-Robe...
KDD
2005
ACM
193views Data Mining» more  KDD 2005»
16 years 7 days ago
An approach to spacecraft anomaly detection problem using kernel feature space
Development of advanced anomaly detection and failure diagnosis technologies for spacecraft is a quite significant issue in the space industry, because the space environment is ha...
Ryohei Fujimaki, Takehisa Yairi, Kazuo Machida