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CIKM
2008
Springer
15 years 8 months ago
Metric-based ontology learning
Ontology learning is an important task in Artificial Intelligence, Semantic Web and Text Mining. This paper presents a novel framework for, and solutions to, three practical probl...
Hui Yang, Jamie Callan
GECCO
2008
Springer
141views Optimization» more  GECCO 2008»
15 years 7 months ago
A study of NK landscapes' basins and local optima networks
We propose a network characterization of combinatorial fitness landscapes by adapting the notion of inherent networks proposed for energy surfaces [5]. We use the well-known fami...
Gabriela Ochoa, Marco Tomassini, Sébastien ...
DPD
2006
123views more  DPD 2006»
15 years 6 months ago
Reducing network traffic in unstructured P2P systems using Top-k queries
A major problem of unstructured P2P systems is their heavy network traffic. This is caused mainly by high numbers of query answers, many of which are irrelevant for users. One solu...
Reza Akbarinia, Esther Pacitti, Patrick Valduriez
TCAD
2008
114views more  TCAD 2008»
15 years 6 months ago
Word-Level Predicate-Abstraction and Refinement Techniques for Verifying RTL Verilog
el Predicate Abstraction and Refinement Techniques for Verifying RTL Verilog Himanshu Jain, Daniel Kroening, Natasha Sharygina, and Edmund M. Clarke, Fellow, IEEE As a first step, ...
Himanshu Jain, Daniel Kroening, Natasha Sharygina,...
TKDE
2010
137views more  TKDE 2010»
15 years 4 months ago
A Survey on Transfer Learning
—A major assumption in many machine learning and data mining algorithms is that the training and future data must be in the same feature space and have the same distribution. How...
Sinno Jialin Pan, Qiang Yang