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AAAI
2008
13 years 10 months ago
Learning and Inference with Constraints
Probabilistic modeling has been a dominant approach in Machine Learning research. As the field evolves, the problems of interest become increasingly challenging and complex. Makin...
Ming-Wei Chang, Lev-Arie Ratinov, Nicholas Rizzolo...
SIGMOD
2007
ACM
125views Database» more  SIGMOD 2007»
14 years 7 months ago
Optimizing mpf queries: decision support and probabilistic inference
Managing uncertain data using probabilistic frameworks has attracted much interest lately in the database literature, and a central computational challenge is probabilistic infere...
Héctor Corrada Bravo, Raghu Ramakrishnan
ESOP
2011
Springer
12 years 11 months ago
Measure Transformer Semantics for Bayesian Machine Learning
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
Johannes Borgström, Andrew D. Gordon, Michael...
ICDE
2009
IEEE
148views Database» more  ICDE 2009»
14 years 9 months ago
Probabilistic Inference over RFID Streams in Mobile Environments
Abstract-- Recent innovations in RFID technology are enabling large-scale cost-effective deployments in retail, healthcare, pharmaceuticals and supply chain management. The advent ...
Thanh Tran 0002, Charles Sutton, Richard Cocci, Ya...
NIPS
2004
13 years 9 months ago
Probabilistic Inference of Alternative Splicing Events in Microarray Data
Alternative splicing (AS) is an important and frequent step in mammalian gene expression that allows a single gene to specify multiple products, and is crucial for the regulation ...
Ofer Shai, Brendan J. Frey, Quaid Morris, Qun Pan,...