Regularization in matrix relevance learning

IEEE Transactions on Neural Networks

Volumn 21, Issue 5, 2010, Pages 831-840

  Schneider, Petra ^a   Bunte, Kerstin ^a   Stiekema, Han ^a   Hammer, Barbara ^b   Villmann, Thomas ^c   Biehl, Michael ^a  

^a UNIVERSITY OF GRONINGEN   (Netherlands)

^b BIELEFELD UNIVERSITY   (Germany)

^c UNIVERSITY OF APPLIED SCIENCES MITTWEIDA   (Germany)

Author keywords

Cost function; Learning vector quantization (LVQ); Metric adaptation; Regularization

Indexed keywords

ADAPTIVE DISTANCE MEASURE; BENCHMARK CLASSIFICATION; DATA SETS; FEATURE SPACE; GENERALIZATION ABILITY; LEARNING SCHEMES; LEARNING VECTOR QUANTIZATION; LOW-DIMENSIONAL REPRESENTATION; MACHINE-LEARNING; MATRIX; METRIC ADAPTATION; METRIC LEARNING; MODEL DATA; REGULARIZATION TECHNIQUE; RELEVANCE LEARNING; UCI REPOSITORY;

CLASSIFICATION (OF INFORMATION); COST FUNCTIONS; MATRIX ALGEBRA; VECTOR QUANTIZATION;

LEARNING ALGORITHMS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; FEEDBACK SYSTEM; HUMAN; LEARNING; PHYSIOLOGY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; FEEDBACK; HUMANS; LEARNING; NEURAL NETWORKS (COMPUTER);

EID: 77951917542     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2010.2042729     Document Type: Article

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