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NIPS
2004
13 years 8 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,...
ICDM
2010
IEEE
150views Data Mining» more  ICDM 2010»
13 years 5 months ago
Probabilistic Inference Protection on Anonymized Data
Background knowledge is an important factor in privacy preserving data publishing. Probabilistic distributionbased background knowledge is a powerful kind of background knowledge w...
Raymond Chi-Wing Wong, Ada Wai-Chee Fu, Ke Wang, Y...
ICML
2004
IEEE
14 years 8 months ago
Variational methods for the Dirichlet process
Variational inference methods, including mean field methods and loopy belief propagation, have been widely used for approximate probabilistic inference in graphical models. While ...
David M. Blei, Michael I. Jordan
ISIPTA
2005
IEEE
168views Mathematics» more  ISIPTA 2005»
14 years 1 months ago
Approximate Inference in Credal Networks by Variational Mean Field Methods
Graph-theoretical representations for sets of probability measures (credal networks) generally display high complexity, and approximate inference seems to be a natural solution fo...
Jaime Shinsuke Ide, Fabio Gagliardi Cozman
CORR
2012
Springer
170views Education» more  CORR 2012»
12 years 3 months ago
What Cannot be Learned with Bethe Approximations
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
Uri Heinemann, Amir Globerson