Abstract
We consider the Independent Subspace Analysis problem from the point of view of contrast functions, showing that contrast functions are able to partially solve the ISA problem. That is, basic ICA can solve the ISA problem up to within-subspace separation/analysis. We define sub- and super-Gaussian subspaces and extend to ISA a previous result on freedom of ICA from local optima. We also consider new types of dependent densities that satisfy or violate the entropy power inequality (EPI) condition.
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Palmer, J.A., Makeig, S. (2012). Contrast Functions for Independent Subspace Analysis. In: Theis, F., Cichocki, A., Yeredor, A., Zibulevsky, M. (eds) Latent Variable Analysis and Signal Separation. LVA/ICA 2012. Lecture Notes in Computer Science, vol 7191. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28551-6_15
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DOI: https://doi.org/10.1007/978-3-642-28551-6_15
Publisher Name: Springer, Berlin, Heidelberg
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