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SIGIR
2008
ACM
13 years 8 months ago
Learning to rank with partially-labeled data
Ranking algorithms, whose goal is to appropriately order a set of objects/documents, are an important component of information retrieval systems. Previous work on ranking algorith...
Kevin Duh, Katrin Kirchhoff
ICSE
2004
IEEE-ACM
14 years 8 months ago
Generating Tests from Counterexamples
We have extended the software model checker BLAST to automatically generate test suites that guarantee full coverage with respect to a given predicate. More precisely, given a C p...
Dirk Beyer, Adam J. Chlipala, Thomas A. Henzinger,...
ICTAI
2007
IEEE
14 years 2 months ago
Establishing Logical Rules from Empirical Data
We review a method of generating logical rules, or axioms, from empirical data. This method, using closed set properties of formal concept analysis, has been previously described ...
John L. Pfaltz
IJCNN
2006
IEEE
14 years 2 months ago
Predicting Juvenile Diabetes from Clinical Test Results
—Two approaches to building models for prediction of the onset of Type 1 diabetes mellitus in juvenile subjects were examined. A set of tests performed immediately before diagnos...
Shibendra S. Pobi, Lawrence O. Hall
ECML
2007
Springer
14 years 2 months ago
Learning to Classify Documents with Only a Small Positive Training Set
Many real-world classification applications fall into the class of positive and unlabeled (PU) learning problems. In many such applications, not only could the negative training ex...
Xiaoli Li, Bing Liu, See-Kiong Ng