A training algorithm for optimal margin classifiers
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Nonlinear component analysis as a kernel eigenvalue problem
Neural Computation
Iterative Kernel Principal Component Analysis for Image Modeling
IEEE Transactions on Pattern Analysis and Machine Intelligence
Resolving Hidden Representations
Neural Information Processing
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This paper presents a linear replicator [2][4] based on minimizing the reconstruction error [8][9] It can be used to study the learning behaviors of the kernel principal component analysis [10], the Hebbian algorithm for the principle component analysis (PCA) [8][9] and the iterative kernel PCA [3].