Expectation propagation for bayesian multi-task feature selection

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6321 LNAI, Issue PART 1, 2010, Pages 522-537

  Hernández Lobato, Daniel ^a   Hernández Lobato, José Miguel ^b   Helleputte, Thibault ^a   Dupont, Pierre ^a  

^a UNIVERSITÉ CATHOLIQUE DE LOUVAIN   (Belgium)

^b UNIVERSIDAD AUTÓNOMA DE MADRID   (Spain)

Author keywords

approximate Bayesian inference; expectation propagation; feature selection; Multi task learning

Indexed keywords

APPROXIMATE BAYESIAN INFERENCE; APPROXIMATE INFERENCE; BAYESIAN; BAYESIAN INFERENCE; BAYESIAN MODEL; DATA POOLING; DATA SETS; EXPECTATION PROPAGATION; FEATURE SELECTION; MULTITASK LEARNING; PARAMETRIZATIONS; POSTERIOR DISTRIBUTIONS; SPARSE PRIOR; TASK LEARNING; TRAINING DATA; TWO-STATE;

BAYESIAN NETWORKS; COMPUTATIONAL COMPLEXITY; COMPUTATIONAL EFFICIENCY; INFERENCE ENGINES; LEARNING SYSTEMS; PROBABILITY DISTRIBUTIONS;

FEATURE EXTRACTION;

EID: 78049339967     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15880-3_39     Document Type: Conference Paper

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