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IDA
2009
Springer
13 years 7 months ago
Hierarchical Extraction of Independent Subspaces of Unknown Dimensions
Abstract. Independent Subspace Analysis (ISA) is an extension of Independent Component Analysis (ICA) that aims to linearly transform a random vector such as to render groups of it...
Peter Gruber, Harold W. Gutch, Fabian J. Theis
SDM
2007
SIAM
133views Data Mining» more  SDM 2007»
13 years 11 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
CORR
2008
Springer
63views Education» more  CORR 2008»
13 years 10 months ago
Testing Statistical Hypotheses About Ergodic Processes
We propose a method for statistical analysis of time series, that allows us to obtain solutions to some classical problems of mathematical statistics under the only assumption tha...
Daniil Ryabko, Boris Ryabko
COLT
2010
Springer
13 years 7 months ago
Principal Component Analysis with Contaminated Data: The High Dimensional Case
We consider the dimensionality-reduction problem (finding a subspace approximation of observed data) for contaminated data in the high dimensional regime, where the number of obse...
Huan Xu, Constantine Caramanis, Shie Mannor
NECO
2008
122views more  NECO 2008»
13 years 9 months ago
Constrained Subspace ICA Based on Mutual Information Optimization Directly
We introduce a new approach to constrained Independent Component Analysis (ICA) by formulating the original, unconstrained ICA problem as well as the constraints in mutual informa...
Marc M. Van Hulle