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» Two Techniques to Improve Finite Model Search
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CPAIOR
2008
Springer
13 years 9 months ago
Fitness-Distance Correlation and Solution-Guided Multi-point Constructive Search for CSPs
Solution-Guided Multi-Point Constructive Search (SGMPCS) is a complete, constructive search technique that has been shown to out-perform standard constructive search techniques on ...
Ivan Heckman, J. Christopher Beck
BMCBI
2010
95views more  BMCBI 2010»
13 years 8 months ago
Modelling p-value distributions to improve theme-driven survival analysis of cancer transcriptome datasets
Background: Theme-driven cancer survival studies address whether the expression signature of genes related to a biological process can predict patient survival time. Although this...
Esteban Czwan, Benedikt Brors, David Kipling
ECAI
2008
Springer
13 years 9 months ago
Justification-Based Non-Clausal Local Search for SAT
While stochastic local search (SLS) techniques are very efficient in solving hard randomly generated propositional satisfiability (SAT) problem instances, a major challenge is to i...
Matti Järvisalo, Tommi A. Junttila, Ilkka Nie...
WSDM
2010
ACM
245views Data Mining» more  WSDM 2010»
14 years 5 months ago
Improving Quality of Training Data for Learning to Rank Using Click-Through Data
In information retrieval, relevance of documents with respect to queries is usually judged by humans, and used in evaluation and/or learning of ranking functions. Previous work ha...
Jingfang Xu, Chuanliang Chen, Gu Xu, Hang Li, Elbi...
ICPR
2008
IEEE
14 years 2 months ago
Fast model selection for MaxMinOver-based training of support vector machines
OneClassMaxMinOver (OMMO) is a simple incremental algorithm for one-class support vector classification. We propose several enhancements and heuristics for improving model select...
Fabian Timm, Sascha Klement, Thomas Martinetz