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» Set cover algorithms for very large datasets
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NIPS
2001
13 years 9 months ago
A Parallel Mixture of SVMs for Very Large Scale Problems
Support Vector Machines (SVMs) are currently the state-of-the-art models for many classication problems but they suer from the complexity of their training algorithm which is at l...
Ronan Collobert, Samy Bengio, Yoshua Bengio
IVS
2002
106views more  IVS 2002»
13 years 8 months ago
Pixel bar charts: a visualization technique for very large multi-attribute data sets?
Simple presentation graphics are intuitive and easy-to-use, but show only highly aggregated data presenting only a very small number of data values (as in the case of bar charts) ...
Daniel A. Keim, Ming C. Hao, Umeshwar Dayal, Meich...
TASE
2010
IEEE
13 years 3 months ago
Coverage of a Planar Point Set With Multiple Robots Subject to Geometric Constraints
This paper focuses on the assignment of discrete points among K robots and determining the order in which the points should be processed by the robots, in the presence of geometric...
Nilanjan Chakraborty, Srinivas Akella, John T. Wen
AUSAI
2003
Springer
14 years 1 months ago
Efficiently Mining Frequent Patterns from Dense Datasets Using a Cluster of Computers
Efficient mining of frequent patterns from large databases has been an active area of research since it is the most expensive step in association rules mining. In this paper, we pr...
Yudho Giri Sucahyo, Raj P. Gopalan, Amit Rudra
SIGMOD
1996
ACM
151views Database» more  SIGMOD 1996»
14 years 16 days ago
BIRCH: An Efficient Data Clustering Method for Very Large Databases
Finding useful patterns in large datasets has attracted considerable interest recently, and one of the most widely st,udied problems in this area is the identification of clusters...
Tian Zhang, Raghu Ramakrishnan, Miron Livny