Multi-task learning for analyzing and sorting large databases of sequential data

IEEE Transactions on Signal Processing

Volumn 56, Issue 8 II, 2008, Pages 3918-3931

  Ni, Kai ^a   Paisley, John ^a   Carin, Lawrence ^a   Dunson, David ^a  

^a Duke University   (United States)

Author keywords

Hierarchical Bayesian modeling; Infinite hidden Markov model (iHMM); Multi task learning (MTL); Variational Bayesian (VB)

Indexed keywords

BAYESIAN NETWORKS; DATABASE SYSTEMS; EDUCATION; HIDDEN MARKOV MODELS; INFORMATION ANALYSIS; LEARNING SYSTEMS; LINEARIZATION; MARKOV PROCESSES; MECHANISMS;

AFFINITY MATRIX; BAYESIAN FRAMEWORKS; DATA SETS; DATA SHARING; DIGITAL MUSIC; DIRICHLET; HIERARCHICAL BAYESIAN MODELING; INFINITE HIDDEN MARKOV MODEL; INFINITE HIDDEN MARKOV MODEL (IHMM); LARGE DATABASES; MODEL SELECTIONS; MTL METHOD; MULTI-TASK LEARNING; MULTI-TASK LEARNING (MTL); MULTIPLE TASKING; MUSIC CLIPS; NESTED DIRICHLET PROCESS; NON-PARAMETRIC; NUMBER OF STATES; SEQUENTIAL DATA; SPEED UPS; VARIATIONAL BAYESIAN; VARIATIONAL BAYESIAN (VB);

SORTING;

EID: 48849102964     PISSN: 1053587X     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSP.2008.924798     Document Type: Article

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