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» Computational Modeling and Complexity Science
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FOCS
1990
IEEE
15 years 11 months ago
Separating Distribution-Free and Mistake-Bound Learning Models over the Boolean Domain
Two of the most commonly used models in computational learning theory are the distribution-free model in which examples are chosen from a fixed but arbitrary distribution, and the ...
Avrim Blum
LICS
2005
IEEE
16 years 12 days ago
Model Checking Vs. Generalized Model Checking: Semantic Minimizations for Temporal Logics
Three-valued models, in which properties of a system are either true, false or unknown, have recently been advocated as a better representation for reactive program abstractions g...
Patrice Godefroid, Michael Huth
IVCNZ
1998
15 years 8 months ago
On Comparing Two Scenarios for Probabilistic Image Modelling
Traditional scenario of probabilistic modelling is directed at generating samples having a given probability distribution. We argue that this scenario is impracticable for image m...
Georgy L. Gimel'farb
IEEESP
2011
14 years 10 months ago
On Adversary Models and Compositional Security
We present a representative development in the science of security that includes a generic model of computer systems, their security properties and adversaries who actively interf...
Anupam Datta, Jason Franklin, Deepak Garg, Limin J...
195
Voted
BMCBI
2005
246views more  BMCBI 2005»
15 years 6 months ago
ParPEST: a pipeline for EST data analysis based on parallel computing
Background: Expressed Sequence Tags (ESTs) are short and error-prone DNA sequences generated from the 5' and 3' ends of randomly selected cDNA clones. They provide an im...
Nunzio D'Agostino, Mario Aversano, Maria Luisa Chi...