Kernel topic models

Journal of Machine Learning Research

Volumn 22, Issue , 2012, Pages 511-519

  Hennig, Philipp ^a,b,c   Stern, David ^c   Herbrich, Ralf ^c,d   Graepel, Thore ^c  

^a UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^b MAX PLANCK INSTITUTE FOR INTELLIGENT SYSTEMS   (Germany)

^c MICROSOFT RESEARCH   (United States)

^d FACEBOOK   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION ALGORITHMS; ARTIFICIAL INTELLIGENCE; MIXTURES; PRINCIPAL COMPONENT ANALYSIS; STATISTICS;

APPROXIMATE ALGORITHMS; APPROXIMATE INFERENCE; DISCRETE DISTRIBUTION; GAUSSIAN PROCESSES; LAPLACE APPROXIMATION; LATENT DIRICHLET ALLOCATION; LATENT VARIABLE MODELING; TOPIC MODELING;

GAUSSIAN DISTRIBUTION;

EID: 84954513532     PISSN: 15324435     EISSN: 15337928     Source Type: Journal    
DOI: None     Document Type: Conference Paper

References (21)

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