Discovery of exogenous variables in data with more variables than observations

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

Volumn 6352 LNCS, Issue PART 1, 2010, Pages 67-76

  Sogawa, Yasuhiro ^a   Shimizu, Shohei ^a   Hyvärinen, Aapo ^b   Washio, Takashi ^a   Shimamura, Teppei ^c   Imoto, Seiya ^c  

^a OSAKA UNIVERSITY   (Japan)

^b UNIVERSITY OF HELSINKI   (Finland)

^c UNIVERSITY OF TOKYO   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL DATA; CAUSAL CHAINS; CAUSAL MODEL; CAUSAL MODELING; CLASSICAL SITUATIONS; CONVENTIONAL METHODS; DATA SETS; EFFICIENT EXPERIMENTAL DESIGNS; EXOGENOUS VARIABLES; GENE EXPRESSION DATA; HIGH-DIMENSIONAL; NON-GAUSSIAN; ORDERS OF MAGNITUDE; REAL-WORLD; SAMPLE SIZES;

GENE EXPRESSION; STATISTICS;

NEURAL NETWORKS;

EID: 78049389305     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15819-3_10     Document Type: Conference Paper

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