Maximum covariance unfolding: Manifold learning for bimodal data

Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011

Volumn , Issue , 2011, Pages

  Mahadevan, Vijay ^a   Wong, Chi Wah ^b   Pereira, Jose Costa ^a   Liu, Thomas T ^b   Vasconcelos, Nuno ^a   Saul, Lawrence K ^c  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

GRAPH THEORY; LEARNING ALGORITHMS; MATHEMATICAL TRANSFORMATIONS; MICROCONTROLLERS;

BI-MODAL DATA; CROSS-MODAL; DIMENSIONALITY REDUCTION; HIGH-DIMENSIONAL; HIGHER-DIMENSIONAL; INPUT MODALITIES; LOW DIMENSIONAL EMBEDDING; MANIFOLD LEARNING; MANIFOLD LEARNING ALGORITHM; UNFOLDINGS;

LINEAR PROGRAMMING;

EID: 85162560954     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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