Exploratory observation machine (XOM) with kullback-leibler divergence for dimensionality reduction and visualization

Proceedings of the 18th European Symposium on Artificial Neural Networks - Computational Intelligence and Machine Learning, ESANN 2010

Volumn , Issue , 2010, Pages 87-92

  Bunte, Kerstin ^a,b   Hammer, Barbara ^c   Villmann, Thomas ^d   Biehl, Michael ^b   Wismüller, Axel ^a  

^a UNIVERSITY OF ROCHESTER   (United States)

^b UNIVERSITY OF GRONINGEN   (Netherlands)

^c BIELEFELD UNIVERSITY   (Germany)

^d UNIVERSITY OF APPLIED SCIENCES MITTWEIDA   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL EXPENSE; DIMENSIONALITY REDUCTION; KULLBACK LEIBLER DIVERGENCE; NEIGHBORHOOD FUNCTION; OPTIMIZATION APPROACH; SCIENCE AND ENGINEERING; STRUCTURE-PRESERVING; TOPOLOGY-PRESERVING MAPPINGS;

LEARNING SYSTEMS;

NEURAL NETWORKS;

EID: 84887014256     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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