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OSDI
2006
ACM
14 years 5 months ago
From Uncertainty to Belief: Inferring the Specification Within
Automatic tools for finding software errors require a set of specifications before they can check code: if they do not know what to check, they cannot find bugs. This paper presen...
Ted Kremenek, Paul Twohey, Godmar Back, Andrew Y. ...
PODS
2006
ACM
156views Database» more  PODS 2006»
14 years 5 months ago
From statistical knowledge bases to degrees of belief: an overview
An intelligent agent will often be uncertain about various properties of its environment, and when acting in that environment it will frequently need to quantify its uncertainty. ...
Joseph Y. Halpern
ESANN
2007
13 years 6 months ago
How to process uncertainty in machine learning?
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Barbara Hammer, Thomas Villmann
ECSQARU
2005
Springer
13 years 10 months ago
Conditional Deduction Under Uncertainty
Conditional deduction in binary logic basically consists of deriving new statements from an existing set of statements and conditional rules. Modus Ponens, which is the classical e...
Audun Jøsang, Simon Pope, Milan Daniel
IJAR
2007
87views more  IJAR 2007»
13 years 4 months ago
Pruning belief decision tree methods in averaging and conjunctive approaches
The belief decision tree (BDT) approach is a decision tree in an uncertain environment where the uncertainty is represented through the Transferable Belief Model (TBM), one interp...
Salsabil Trabelsi, Zied Elouedi, Khaled Mellouli