A Bayesian approach to switching linear Gaussian state-space models for unsupervised time-series segmentation

Proceedings - 7th International Conference on Machine Learning and Applications, ICMLA 2008

Volumn , Issue , 2008, Pages 3-9

  Chiappa, Silvia ^a  

^a MAX PLANCK INSTITUTE FOR BIOLOGICAL CYBERNETICS   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

APPLICATIONS; APPROXIMATION ALGORITHMS; INFERENCE ENGINES; ROBOT LEARNING; TIME SERIES; TRELLIS CODES;

A-PRIORI; BAYESIAN APPROACHES; FUNDAMENTAL PROBLEMS; GAUSSIAN STATE; INFERENCE ALGORITHMS; MODEL-BASED; NON-BAYESIAN APPROACHES; PARAMETRIZATION; TIME-SERIES SEGMENTATIONS; VARIATIONAL APPROXIMATIONS;

BAYESIAN NETWORKS;

EID: 60649104620     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICMLA.2008.109     Document Type: Conference Paper

References (13)

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