Bayesian online multitask learning of gaussian processes

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 32, Issue 2, 2010, Pages 193-205

  Pillonetto, Gianluigi ^a   Dinuzzo, Francesco ^b   De Nicolao, Giuseppe ^b  

^a UNIVERSITY OF PADOVA   (Italy)

^b UNIVERSITY OF PAVIA   (Italy)

Author keywords

Collaborative filtering; Gaussian processes; Kalman filtering; Kernel methods; Mixed effects model; Multitask learning; Pharmacokinetic data.; Regularization

Indexed keywords

COLLABORATIVE FILTERING; GAUSSIAN PROCESSES; KALMAN-FILTERING; MIXED EFFECTS MODELS; MULTITASK LEARNING; PHARMACOKINETIC DATA;

BAYESIAN NETWORKS; BIOCHEMISTRY; COMPUTATIONAL COMPLEXITY; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); KALMAN FILTERS; PHARMACOKINETICS;

COMPUTATIONAL EFFICIENCY;

XENOBIOTIC AGENT;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; COMPUTER SIMULATION; GLUCOSE BLOOD LEVEL; HUMAN; METABOLISM; NORMAL DISTRIBUTION; PHARMACOKINETICS;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; BLOOD GLUCOSE; COMPUTER SIMULATION; HUMANS; NORMAL DISTRIBUTION; PHARMACOKINETICS; XENOBIOTICS;

EID: 73849084587     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2008.297     Document Type: Article

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