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» A New Autocalibration Algorithm: Experimental Evaluation
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DEXAW
2010
IEEE
196views Database» more  DEXAW 2010»
13 years 7 months ago
Direct Optimization of Evaluation Measures in Learning to Rank Using Particle Swarm
— One of the central issues in Learning to Rank (L2R) for Information Retrieval is to develop algorithms that construct ranking models by directly optimizing evaluation measures ...
Ósscar Alejo, Juan M. Fernández-Luna...
DLOG
2010
13 years 5 months ago
TBox Classification in Parallel: Design and First Evaluation
Abstract. One of the most frequently used inference services of description logic reasoners classifies all named classes of OWL ontologies into a subsumption hierarchy. Due to emer...
Mina Aslani, Volker Haarslev
GECCO
2007
Springer
159views Optimization» more  GECCO 2007»
14 years 1 months ago
Objective fitness correlation
This paper introduces the Objective Fitness Correlation, a new tool to analyze the evaluation accuracy of coevolutionary algorithms. Accurate evaluation is an essential ingredient...
Edwin D. de Jong
CORR
2012
Springer
209views Education» more  CORR 2012»
12 years 3 months ago
Densest Subgraph in Streaming and MapReduce
The problem of finding locally dense components of a graph is an important primitive in data analysis, with wide-ranging applications from community mining to spam detection and ...
Bahman Bahmani, Ravi Kumar, Sergei Vassilvitskii
ICDCS
2008
IEEE
14 years 2 months ago
Fair K Mutual Exclusion Algorithm for Peer to Peer Systems
k-mutual exclusion is an important problem for resourceintensive peer-to-peer applications ranging from aggregation to file downloads. In order to be practically useful, k-mutual...
Vijay Anand Reddy, Prateek Mittal, Indranil Gupta