Sciweavers

1403 search results - page 8 / 281
» Set cover algorithms for very large datasets
Sort
View
SEMWEB
2010
Springer
13 years 6 months ago
Optimize First, Buy Later: Analyzing Metrics to Ramp-Up Very Large Knowledge Bases
As knowledge bases move into the landscape of larger ontologies and have terabytes of related data, we must work on optimizing the performance of our tools. We are easily tempted t...
Paea LePendu, Natalya Fridman Noy, Clement Jonquet...
ICML
2005
IEEE
14 years 9 months ago
Core Vector Regression for very large regression problems
In this paper, we extend the recently proposed Core Vector Machine algorithm to the regression setting by generalizing the underlying minimum enclosing ball problem. The resultant...
Ivor W. Tsang, James T. Kwok, Kimo T. Lai
CSC
2008
13 years 9 months ago
Efficient and Effective Practical Algorithms for the Set-Covering Problem
- The set-covering problem is an interesting problem in computational complexity theory. In [1], the setcovering problem has been proved to be NP hard and a greedy heuristic algori...
Qi Yang, Jamie McPeek, Adam Nofsinger
ICDE
2000
IEEE
95views Database» more  ICDE 2000»
14 years 9 months ago
Dynamic Histograms: Capturing Evolving Data Sets
In this paper, we introduce dynamic histograms, which are constructed and maintained incrementally. We develop several dynamic histogram construction algorithms and show that they...
Donko Donjerkovic, Yannis E. Ioannidis, Raghu Rama...
ICDM
2006
IEEE
161views Data Mining» more  ICDM 2006»
14 years 2 months ago
Hierarchical Density Shaving: A clustering and visualization framework for large biological datasets
In many clustering applications for bioinformatics, only part of the data clusters into one or more groups while the rest needs to be pruned. For such situations, we present Hiera...
Gunjan Gupta, Alexander Liu, Joydeep Ghosh