Limited Rank Matrix Learning, discriminative dimension reduction and visualization

Neural Networks

Volumn 26, Issue , 2012, Pages 159-173

  Bunte, Kerstin ^a   Schneider, Petra ^b   Hammer, Barbara ^c   Schleif, Frank Michael ^c   Villmann, Thomas ^d   Biehl, Michael ^a  

^a UNIVERSITY OF GRONINGEN   (Netherlands)

^b UNIVERSITY OF BIRMINGHAM   (United Kingdom)

^c BIELEFELD UNIVERSITY   (Germany)

^d UNIVERSITY OF APPLIED SCIENCES MITTWEIDA   (Germany)

Author keywords

Adaptive metrics; Classification; Dimension reduction; Learning Vector Quantization; Visualization

Indexed keywords

ADAPTIVE METRICS; ADAPTIVE PARAMETERS; COMPUTATION TIME; DIMENSION REDUCTION; DISTANCE MEASURE; GENERALIZED MATRIX; INTEGRAL PART; INTRINSIC DIMENSIONS; LABELED DATA; LEARNING VECTOR QUANTIZATION; LEARNING VECTOR QUANTIZATION ALGORITHMS; LOW-DIMENSIONAL REPRESENTATION; MATRIX; MEMORY REQUIREMENTS; PRE-PROCESSING STEP; PRIOR KNOWLEDGE; REAL WORLD DATA; SQUARE MATRICES; VISUALIZATION METHOD;

CLASSIFICATION (OF INFORMATION); CLUSTERING ALGORITHMS; DATA VISUALIZATION; FLOW VISUALIZATION; VECTOR QUANTIZATION; VISUALIZATION;

MATRIX ALGEBRA;

ARTICLE; CLASSIFICATION ALGORITHM; DISCRIMINANT ANALYSIS; GENERALIZED MATRIX LEARNING VECTOR QUANTIZATION ALGORITHM; LEARNING ALGORITHM; MATHEMATICAL ANALYSIS; MATHEMATICAL MODEL; PRIORITY JOURNAL; PROCESS OPTIMIZATION; REMOTE SENSING; STATISTICS;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; DISCRIMINANT ANALYSIS; HUMANS; LEARNING; PATTERN RECOGNITION, AUTOMATED;

EID: 84855962168     PISSN: 08936080     EISSN: 18792782     Source Type: Journal    
DOI: 10.1016/j.neunet.2011.10.001     Document Type: Article

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