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» Set cover algorithms for very large datasets
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WWW
2010
ACM
16 years 1 months ago
Mind the data skew: distributed inferencing by speeddating in elastic regions
Semantic Web data exhibits very skewed frequency distributions among terms. Efficient large-scale distributed reasoning methods should maintain load-balance in the face of such hi...
Spyros Kotoulas, Eyal Oren, Frank van Harmelen
CIKM
2009
Springer
16 years 21 days ago
Semi-nonnegative matrix factorization with global statistical consistency for collaborative filtering
Collaborative Filtering, considered by many researchers as the most important technique for information filtering, has been extensively studied by both academic and industrial co...
Hao Ma, Haixuan Yang, Irwin King, Michael R. Lyu
AIIA
2005
Springer
15 years 11 months ago
Towards Fault-Tolerant Formal Concept Analysis
Given Boolean data sets which record properties of objects, Formal Concept Analysis is a well-known approach for knowledge discovery. Recent application domains, e.g., for very lar...
Ruggero G. Pensa, Jean-François Boulicaut
AAAI
1998
15 years 7 months ago
Boosting in the Limit: Maximizing the Margin of Learned Ensembles
The "minimum margin" of an ensemble classifier on a given training set is, roughly speaking, the smallest vote it gives to any correct training label. Recent work has sh...
Adam J. Grove, Dale Schuurmans
183
Voted
PR
2010
135views more  PR 2010»
15 years 27 days ago
Revisiting priority queues for image analysis
Many algorithms in image analysis require a priority queue, a data structure that holds pointers to pixels in the image, and which allows efficiently finding the pixel in the queu...
Cris L. Luengo Hendriks