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ML
2006
ACM
131views Machine Learning» more  ML 2006»
14 years 11 months ago
Markov logic networks
We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge b...
Matthew Richardson, Pedro Domingos
AIPS
1996
15 years 9 days ago
Building a Planner for Information Gathering: A Report from the Trenches
Informationgathering requires locating and integrating data froma set of distributed informationsources. These sources maycontain overlapping data and can comefrom different types...
Craig A. Knoblock
VMCAI
2005
Springer
15 years 4 months ago
On the Complexity of Error Explanation
When a system fails to satisfy its specification, the model checker produces an error trace (or counter-example) that demonstrates an undesirable behavior, which is then used in d...
Nirman Kumar, Viraj Kumar, Mahesh Viswanathan
WCRE
2006
IEEE
15 years 5 months ago
Extracting Output Formats from Executables
We describe the design and implementation of FFE/x86 (File-Format Extractor for x86), an analysis tool that works on stripped executables (i.e., neither source code nor debugging ...
Junghee Lim, Thomas W. Reps, Ben Liblit
CLUSTER
2008
IEEE
15 years 5 months ago
Empirical-based probabilistic upper bounds for urgent computing applications
—Scientific simulation and modeling often aid in making critical decisions in such diverse fields as city planning, severe weather prediction and influenza modeling. In some o...
Nick Trebon, Peter H. Beckman