Learning a tensor subspace for semi-supervised dimensionality reduction

Soft Computing

Volumn 15, Issue 2, 2011, Pages 383-395

  Zhang, Zhao ^a   Ye, Ning ^a,b  

^a NANJING FORESTRY UNIVERSITY   (China)

^b SHANDONG UNIVERSITY   (China)

Author keywords

Dimensionality reduction; Image recognition; Pairwise similarity and dissimilarity constraints; Semi supervised learning; Tensor representation

Indexed keywords

BELONG TO; CLASSIFICATION ACCURACY; DIMENSIONALITY REDUCTION; DIMENSIONALITY REDUCTION ALGORITHMS; DOMAIN KNOWLEDGE; EIGEN DECOMPOSITION; GLOBAL STRUCTURE; HIGH DIMENSIONAL DATA; INTRINSIC STRUCTURES; NUMERICAL RESULTS; PAIRWISE SIMILARITY AND DISSIMILARITY CONSTRAINTS; REAL-WORLD APPLICATION; SECOND-ORDER TENSORS; SEMI-SUPERVISED; SEMI-SUPERVISED LEARNING; SPATIAL LOCALITY; TENSOR REPRESENTATION; TENSOR SUBSPACE LEARNING; UNBALANCED DATA; UNLABELED SAMPLES; VECTOR PATTERNS; VECTOR REPRESENTATIONS;

CLASSIFICATION (OF INFORMATION); IMAGE RECOGNITION; PIXELS; SUPERVISED LEARNING; VECTORS;

TENSORS;

EID: 79953877901     PISSN: 14327643     EISSN: 14337479     Source Type: Journal    
DOI: 10.1007/s00500-010-0631-x     Document Type: Article

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