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164
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ICDE
2012
IEEE
13 years 6 months ago
2012
IEEE
—Outlier mining is a major task in data analysis. Outliers are objects that highly deviate from regular objects in their local neighborhood. Density-based outlier ranking methods...
173
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SIGIR
2012
ACM
13 years 6 months ago
2012
ACM
In crowdsourced relevance judging, each crowd worker typically judges only a small number of examples, yielding a sparse and imbalanced set of judgments in which relatively few wo...
134
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AIMSA
2008
Springer
15 years 10 months ago
2008
Springer
Relational instance-based learning (RIBL) algorithms offer high prediction capabilities. However, they do not scale up well, specially in domains where there is a time bound for c...
134
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CIKM
2011
Springer
14 years 3 months ago
2011
Springer
Many large-scale Web applications that require ranked top-k retrieval are implemented using inverted indices. An inverted index represents a sparse term-document matrix, where non...
149
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GECCO
2005
Springer
15 years 9 months ago
2005
Springer
In neuroevolution, a genetic algorithm is used to evolve a neural network to perform a particular task. The standard approach is to evolve a population over a number of generation...