A two-stage learning framework of relational Markov networks

Journal of Computational Information Systems

Volumn 6, Issue 4, 2010, Pages 1027-1035

  Wan, Huaiyu ^a   Lin, Youfang ^a   Wu, Zhihao ^a   Huang, Houkuan ^a  

^a BEIJING JIAOTONG UNIVERSITY   (China)

Author keywords

Approximate probabilistic inference; Maximum a posterior; Optimization; Relational Markov networks

Indexed keywords

APPROXIMATE INFERENCE; CLASSIFICATION TASKS; CONJUGATE GRADIENT; CONVERGENCE SPEED; INTEGRATING INFORMATION; JOINT PROBABILISTIC; LEARNING FRAMEWORKS; LINK ATTRIBUTES; MARKOV NETWORKS; MARKOV RANDOM FIELDS; MAXIMUM A POSTERIORS; OPTIMIZATION ALGORITHMS; PROBABILISTIC INFERENCE; RELATIONAL DATA; TRAINING PROCESS; TRAINING TIME; TWO STAGE;

COMPUTATIONAL COMPLEXITY; CONJUGATE GRADIENT METHOD; CONVERGENCE OF NUMERICAL METHODS; INFERENCE ENGINES; OPTIMIZATION;

LEARNING ALGORITHMS;

EID: 77956953423     PISSN: 15539105     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

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