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ICPP
1991
IEEE
15 years 4 months ago
Automatic Parallel Program Generation and Optimization from Data Decompositions
Data decomposition is probably the most successful method for generating parallel programs. In this paper a general framework is described for the automatic generation of parallel...
Edwin M. R. M. Paalvast, Henk J. Sips, Arjan J. C....
LPNMR
2009
Springer
15 years 5 months ago
Belief Logic Programming: Uncertainty Reasoning with Correlation of Evidence
Abstract. Belief Logic Programming (BLP) is a novel form of quantitative logic programming in the presence of uncertain and inconsistent information, which was designed to be able ...
Hui Wan, Michael Kifer
MP
2006
175views more  MP 2006»
15 years 1 months ago
Conditional Value-at-Risk in Stochastic Programs with Mixed-Integer Recourse
In classical two-stage stochastic programming the expected value of the total costs is minimized. Recently, mean-risk models - studied in mathematical finance for several decades -...
Rüdiger Schultz, Stephan Tiedemann
AAAI
1997
15 years 2 months ago
Effective Bayesian Inference for Stochastic Programs
In this paper, we propose a stochastic version of a general purpose functional programming language as a method of modeling stochastic processes. The language contains random choi...
Daphne Koller, David A. McAllester, Avi Pfeffer
IWVF
2001
Springer
15 years 5 months ago
Grouping Character Shapes by Means of Genetic Programming
In the framework of an evolutionary approach to machine learning, this paper presents the preliminary version of a learning system that uses Genetic Programming as a tool for autom...
Claudio De Stefano, Antonio Della Cioppa, Angelo M...