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CVPR
2003
IEEE
15 years 11 months ago
Constrained Subspace Modelling
When performing subspace modelling of data using Principal Component Analysis (PCA) it may be desirable to constrain certain directions to be more meaningful in the context of the...
Jaco Vermaak, Patrick Pérez
IDA
2009
Springer
14 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»
14 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
ADAEUROPE
2003
Springer
15 years 1 months ago
Quasar: A New Tool for Concurrent Ada Programs Analysis
Concurrency introduces a high degree of combinatory which may be the source of subtle mistakes. We present a new tool, Quasar, which is based on ASIS and which uses fully the conce...
Sami Evangelista, Claude Kaiser, Jean-Franç...
COLT
2010
Springer
14 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