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» Set cover algorithms for very large datasets
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JCSS
2008
138views more  JCSS 2008»
15 years 4 months ago
Reducing mechanism design to algorithm design via machine learning
We use techniques from sample-complexity in machine learning to reduce problems of incentive-compatible mechanism design to standard algorithmic questions, for a broad class of re...
Maria-Florina Balcan, Avrim Blum, Jason D. Hartlin...
EVOW
2007
Springer
15 years 10 months ago
Reducing the Size of Traveling Salesman Problem Instances by Fixing Edges
Abstract. The Traveling Salesman Problem (TSP) is a well-known NPhard combinatorial optimization problem, for which a large variety of evolutionary algorithms are known. However, t...
Thomas Fischer, Peter Merz
AAAI
2000
15 years 5 months ago
PROMPT: Algorithm and Tool for Automated Ontology Merging and Alignment
Researchers in the ontology-design field have developed the content for ontologies in many domain areas. Recently, ontologies have become increasingly common on the WorldWide Web ...
Natalya Fridman Noy, Mark A. Musen
PAMI
2006
134views more  PAMI 2006»
15 years 4 months ago
A Genetic Algorithm Using Hyper-Quadtrees for Low-Dimensional K-means Clustering
The k-means algorithm is widely used for clustering because of its computational efficiency. Given n points in d-dimensional space and the number of desired clusters k, k-means see...
Michael Laszlo, Sumitra Mukherjee
KDD
2012
ACM
235views Data Mining» more  KDD 2012»
13 years 7 months ago
A near-linear time approximation algorithm for angle-based outlier detection in high-dimensional data
Outlier mining in d-dimensional point sets is a fundamental and well studied data mining task due to its variety of applications. Most such applications arise in high-dimensional ...
Ninh Pham, Rasmus Pagh