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» A Bayesian network framework for reject inference
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NIPS
2003
13 years 9 months ago
On the Concentration of Expectation and Approximate Inference in Layered Networks
We present an analysis of concentration-of-expectation phenomena in layered Bayesian networks that use generalized linear models as the local conditional probabilities. This frame...
XuanLong Nguyen, Michael I. Jordan
ETFA
2008
IEEE
13 years 9 months ago
Efficient failure-free foundry production
Microshrinkages are known as probably the most difficult defects to avoid in high-precission foundry. Depending on the magnitude of this defect, the piece in which it appears must...
Yoseba K. Penya, Pablo Garcia Bringas, Argoitz Zab...
RSFDGRC
2005
Springer
134views Data Mining» more  RSFDGRC 2005»
14 years 1 months ago
The Computational Complexity of Inference Using Rough Set Flow Graphs
Pawlak recently introduced rough set flow graphs (RSFGs) as a graphical framework for reasoning from data. Each rule is associated with three coefficients, which have been shown t...
Cory J. Butz, Wen Yan, Boting Yang
MICAI
2007
Springer
14 years 1 months ago
Optimizing Inference in Bayesian Networks and Semiring Valuation Algebras
Previous work on context-specific independence in Bayesian networks is driven by a common goal, namely to represent the conditional probability tables in a most compact way. In th...
Michael Wachter, Rolf Haenni, Marc Pouly
WCET
2008
13 years 9 months ago
INFER: Interactive Timing Profiles based on Bayesian Networks
We propose an approach for timing analysis of software-based embedded computer systems that builds on the established probabilistic framework of Bayesian networks. We envision an ...
Michael Zolda