Speedy greedy feature selection: Better redshift estimation via massive parallelism

22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2014 - Proceedings

Volumn , Issue , 2014, Pages 87-92

  Gieseke, Fabian ^a   Polsterer, Kai Lars ^b   Oancea, Cosmin Eugen ^a   Igel, Christian ^a  

^a UNIVERSITY OF COPENHAGEN   (Denmark)

^b HEIDELBERG INSTITUTE FOR THEORETICAL STUDIES   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER GRAPHICS; LEARNING SYSTEMS; NEURAL NETWORKS; PROGRAM PROCESSORS;

COMPUTATIONAL SPEED; GRAPHICS PROCESSING UNIT; MASSIVE PARALLELISM; NEAREST NEIGHBOR MODEL; ORDERS OF MAGNITUDE; PARALLEL IMPLEMENTATIONS; RED SHIFT;

FEATURE EXTRACTION;

EID: 84961992292     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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