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» Model Generation for Distributed Java Programs
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UAI
1997
13 years 10 months ago
Robustness Analysis of Bayesian Networks with Local Convex Sets of Distributions
Robust Bayesian inference is the calculation of posterior probability bounds given perturbations in a probabilistic model. This paper focuses on perturbations that can be expresse...
Fabio Gagliardi Cozman
GECCO
2008
Springer
154views Optimization» more  GECCO 2008»
13 years 10 months ago
Automated shape composition based on cell biology and distributed genetic programming
Motivated by the ability of living cells to form specific shapes and structures, we present a computational approach using distributed genetic programming to discover cell-cell i...
Linge Bai, Manolya Eyiyurekli, David E. Breen
ENTCS
2008
146views more  ENTCS 2008»
13 years 9 months ago
Probabilistic Abstract Interpretation of Imperative Programs using Truncated Normal Distributions
istic Abstract Interpretation of Imperative Programs using Truncated Normal Distributions Michael J. A. Smith1 ,2 Laboratory for Foundations of Computer Science University of Edinb...
Michael J. A. Smith
CADE
2005
Springer
14 years 9 months ago
Privacy-Sensitive Information Flow with JML
In today's society, people have very little control over what kinds of personal data are collected and stored by various agencies in both the private and public sectors. We de...
Guillaume Dufay, Amy P. Felty, Stan Matwin
TASE
2007
IEEE
14 years 3 months ago
Model Checking Networked Programs in the Presence of Transmission Failures
Software model checkers work directly on single-process programs, but not on multiple processes. Conversion of processes into threads, combined with a network model, allows for mo...
Cyrille Artho, Christian Sommer 0002, Shinichi Hon...