Online manifold regularization: A new learning setting and empirical study

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5211 LNAI, Issue PART 1, 2008, Pages 393-407

  Goldberg, Andrew B ^a   Li, Ming ^b   Zhu, Xiaojin ^a  

^a University of Wisconsin Madison   (United States)

^b NANJING UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; DATABASE SYSTEMS; INTERNET; LEARNING SYSTEMS; ROBOT LEARNING; STANDARDS; SUPERVISED LEARNING;

CONVEX PROGRAMMINGS; EMPIRICAL STUDIES; GENERALIZATION ACCURACIES; KERNEL SPACES; LEARNING SETTINGS; LEARNING TASKS; ON-LINE LEARNINGS; ONLINE ALGORITHMS; RANDOM PROJECTIONS; REGULARIZATION ALGORITHMS; SEMI-SUPERVISED LEARNINGS; SPARSE APPROXIMATIONS; STOCHASTIC GRADIENT DESCENTS;

EDUCATION;

EID: 56049127186     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-87479-9_44     Document Type: Conference Paper

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