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ESOP
2011
Springer
14 years 10 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...
ICLP
2011
Springer
14 years 10 months ago
Constraints in Non-Boolean Contexts
In high-level constraint modelling languages, constraints can occur in non-Boolean contexts: implicitly, in the form of partial functions, or more explicitly, in the form of const...
Leslie De Koninck, Sebastian Brand, Peter J. Stuck...
PLDI
2011
ACM
14 years 9 months ago
Evaluating value-graph translation validation for LLVM
Translation validators are static analyzers that attempt to verify that program transformations preserve semantics. Normalizing translation validators do so by trying to match the...
Jean-Baptiste Tristan, Paul Govereau, Greg Morrise...
CP
2009
Springer
16 years 7 months ago
Constraint-Based Optimal Testing Using DNNF Graphs
The goal of testing is to distinguish between a number of hypotheses about a systemfor example, dierent diagnoses of faults by applying input patterns and verifying or falsifying t...
Anika Schumann, Martin Sachenbacher, Jinbo Huang
159
Voted
CHI
2003
ACM
16 years 6 months ago
Simple cognitive modeling in a complex cognitive architecture
Cognitive modeling has evolved into a powerful tool for understanding and predicting user behavior. Higher-level modeling frameworks such as GOMS and its variants facilitate fast ...
Dario D. Salvucci, Frank J. Lee