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» Genetic Algorithms for Component Analysis
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SDM
2007
SIAM
133views Data Mining» more  SDM 2007»
15 years 8 months ago
Change-Point Detection using Krylov Subspace Learning
We propose an efficient algorithm for principal component analysis (PCA) that is applicable when only the inner product with a given vector is needed. We show that Krylov subspace...
Tsuyoshi Idé, Koji Tsuda
ICDAR
2011
IEEE
14 years 6 months ago
A New Text-Line Alignment Approach Based on Piece-Wise Painting Algorithm for Handwritten Documents
—Because of writing styles of different individuals, some of the text-lines may be curved in shape. For recognition of such text-lines, their proper alignment is necessary. In th...
Alireza Alaei, P. Nagabhushan, Umapada Pal
TNN
2008
187views more  TNN 2008»
15 years 6 months ago
Complex ICA by Negentropy Maximization
In this paper, we use complex analytic functions to achieve independent component analysis (ICA) by maximization of non-Gaussianity and introduce the complex maximization of nonGau...
Mike Novey, Tülay Adali
ICIP
2008
IEEE
16 years 1 months ago
Correlation Embedding Analysis
—Beyond conventional linear and kernel-based feature extraction, we present a more generalized formulation for feature extraction in this paper. Two representative algorithms usi...
Yun Fu, Thomas S. Huang
SSDBM
2008
IEEE
114views Database» more  SSDBM 2008»
16 years 1 months ago
A General Framework for Increasing the Robustness of PCA-Based Correlation Clustering Algorithms
Abstract. Most correlation clustering algorithms rely on principal component analysis (PCA) as a correlation analysis tool. The correlation of each cluster is learned by applying P...
Hans-Peter Kriegel, Peer Kröger, Erich Schube...