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NECO
2008
83views more  NECO 2008»
13 years 4 months ago
Sequential Fixed-Point ICA Based on Mutual Information Minimization
A new gradient technique is introduced for linear ICA based on the Edgeworth expansion of mutual information, for which the algorithm operates sequentially using fixed-point itera...
Marc M. Van Hulle
ICA
2004
Springer
13 years 10 months ago
Minimax Mutual Information Approach for ICA of Complex-Valued Linear Mixtures
Abstract. Recently, the authors developed the Minimax Mutual Information algorithm for linear ICA of real-valued mixtures, which is based on a density estimate stemming from Jaynes...
Jian-Wu Xu, Deniz Erdogmus, Yadunandana N. Rao, Jo...
NIPS
2001
13 years 6 months ago
MIME: Mutual Information Minimization and Entropy Maximization for Bayesian Belief Propagation
Bayesian belief propagation in graphical models has been recently shown to have very close ties to inference methods based in statistical physics. After Yedidia et al. demonstrate...
Anand Rangarajan, Alan L. Yuille
JMLR
2002
160views more  JMLR 2002»
13 years 4 months ago
Kernel Independent Component Analysis
We present a class of algorithms for independent component analysis (ICA) which use contrast functions based on canonical correlations in a reproducing kernel Hilbert space. On th...
Francis R. Bach, Michael I. Jordan
IBPRIA
2003
Springer
13 years 10 months ago
Does Independent Component Analysis Play a~Role in Unmixing Hyperspectral Data?
—Independent component analysis (ICA) has recently been proposed as a tool to unmix hyperspectral data. ICA is founded on two assumptions: 1) the observed spectrum vector is a li...
José M. P. Nascimento, José M. B. Di...