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» Optimal In-Place Learning and the Lobe Component Analysis
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JMLR
2010
163views more  JMLR 2010»
13 years 2 months ago
Dense Message Passing for Sparse Principal Component Analysis
We describe a novel inference algorithm for sparse Bayesian PCA with a zero-norm prior on the model parameters. Bayesian inference is very challenging in probabilistic models of t...
Kevin Sharp, Magnus Rattray
IDA
2009
Springer
14 years 2 months ago
Estimating Squared-Loss Mutual Information for Independent Component Analysis
Abstract. Accurately evaluating statistical independence among random variables is a key component of Independent Component Analysis (ICA). In this paper, we employ a squared-loss ...
Taiji Suzuki, Masashi Sugiyama
CVPR
2007
IEEE
14 years 9 months ago
Filtered Component Analysis to Increase Robustness to Local Minima in Appearance Models
Appearance Models (AM) are commonly used to model appearance and shape variation of objects in images. In particular, they have proven useful to detection, tracking, and synthesis...
Fernando De la Torre, Alvaro Collet, Manuel Quero,...
NECO
2011
13 years 2 months ago
Least-Squares Independent Component Analysis
Accurately evaluating statistical independence among random variables is a key element of Independent Component Analysis (ICA). In this paper, we employ a squared-loss variant of ...
Taiji Suzuki, Masashi Sugiyama
IJCNN
2006
IEEE
14 years 1 months ago
Relative Gradient Learning for Independent Subspace Analysis
Abstract— Independent subspace analysis (ISA) is a generalization of independent component analysis (ICA), where multidimensional ICA is incorporated with the idea of invariant f...
Heeyoul Choi, Seungjin Choi