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» Measure Transformer Semantics for Bayesian Machine Learning
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83
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ICML
2005
IEEE
15 years 10 months ago
Learning class-discriminative dynamic Bayesian networks
In many domains, a Bayesian network's topological structure is not known a priori and must be inferred from data. This requires a scoring function to measure how well a propo...
John Burge, Terran Lane
ICML
2003
IEEE
15 years 10 months ago
Exploration and Exploitation in Adaptive Filtering Based on Bayesian Active Learning
In the task of adaptive information filtering, a system receives a stream of documents but delivers only those that match a person's information need. As the system filters i...
Yi Zhang, Wei Xu, James P. Callan
ML
2010
ACM
151views Machine Learning» more  ML 2010»
14 years 8 months ago
Inductive transfer for learning Bayesian networks
In several domains it is common to have data from different, but closely related problems. For instance, in manufacturing, many products follow the same industrial process but with...
Roger Luis, Luis Enrique Sucar, Eduardo F. Morales
ICML
2008
IEEE
15 years 10 months ago
Multi-task compressive sensing with Dirichlet process priors
Compressive sensing (CS) is an emerging field that, under appropriate conditions, can significantly reduce the number of measurements required for a given signal. In many applicat...
Yuting Qi, Dehong Liu, David B. Dunson, Lawrence C...
76
Voted
ECML
2006
Springer
15 years 1 months ago
Bayesian Active Learning for Sensitivity Analysis
Abstract. Designs of micro electro-mechanical devices need to be robust against fluctuations in mass production. Computer experiments with tens of parameters are used to explore th...
Tobias Pfingsten