An information geometrical view of stationary subspace analysis

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6792 LNCS, Issue PART 2, 2011, Pages 397-404

  Kawanabe, Motoaki ^a,b   Samek, Wojciech ^a,b   Von Bünau, Paul ^a   Meinecke, Frank C ^a  

^a FRAUNHOFER FIRST   (Germany)

^b TECHNISCHE UNIVERSITÄT BERLIN   (Germany)

Author keywords

generative model; information geometry; Kullback Leibler divergence; maximum likelihood estimation; stationary subspace analysis

Indexed keywords

DATA DISTRIBUTION; GENERATIVE MODEL; HIGH DIMENSIONAL DATA; INFORMATION GEOMETRY; KULLBACK LEIBLER DIVERGENCE; NON-STATIONARITIES; SUBSPACE ANALYSIS; UNSUPERVISED LEARNING METHOD;

INDEPENDENT COMPONENT ANALYSIS; NEURAL NETWORKS; UNSUPERVISED LEARNING;

MAXIMUM LIKELIHOOD ESTIMATION;

EID: 79959326722     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-21738-8_51     Document Type: Conference Paper

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