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AAAI
2008
15 years 1 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»
15 years 11 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
14 years 3 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...
182
Voted
ICDE
2009
IEEE
148views Database» more  ICDE 2009»
16 years 1 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...
92
Voted
NIPS
2004
15 years 1 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,...