Estimating the partition function of graphical models using Langevin importance sampling

Journal of Machine Learning Research

Volumn 31, Issue , 2013, Pages 433-441

  Ma, Jianzhu ^a   Peng, Jian ^a   Wang, Sheng ^a   Xu, Jinbo ^a  

^a TOYOTA TECHNOLOGICAL INSTITUTE AT CHICAGO   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTATIONAL COMPLEXITY; DIFFERENTIAL EQUATIONS; GRAPHIC METHODS; MARKOV PROCESSES; SIMULATED ANNEALING; SPEECH RECOGNITION;

GENERAL GRAPH; GRAPHICAL MODEL; LANGEVIN EQUATION; MARKOV CHAIN MONTE CARLO; PARTITION FUNCTIONS; RANDOM WALK; SAMPLING ALGORITHM; SAMPLING METHOD;

IMPORTANCE SAMPLING;

EID: 84896292146     PISSN: 15324435     EISSN: 15337928     Source Type: Journal    
DOI: None     Document Type: Conference Paper

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