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» Set cover algorithms for very large datasets
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CIKM
2010
Springer
13 years 2 months ago
Set cover algorithms for very large datasets
Graham Cormode, Howard J. Karloff, Anthony Wirth
ICML
2008
IEEE
14 years 5 months ago
Fully distributed EM for very large datasets
In EM and related algorithms, E-step computations distribute easily, because data items are independent given parameters. For very large data sets, however, even storing all of th...
Jason Wolfe, Aria Haghighi, Dan Klein
VLDB
1999
ACM
159views Database» more  VLDB 1999»
13 years 8 months ago
Aggregation Algorithms for Very Large Compressed Data Warehouses
Many efficient algorithms to compute multidimensional aggregation and Cube for relational OLAP have been developed. However, to our knowledge, there is nothing to date in the lite...
Jianzhong Li, Doron Rotem, Jaideep Srivastava
AI
2005
Springer
13 years 10 months ago
A Comparative Study of Two Density-Based Spatial Clustering Algorithms for Very Large Datasets
Spatial clustering is an active research area in spatial data mining with various methods reported. In this paper, we compare two density-based methods, DBSCAN and DBRS. First, we ...
Xin Wang, Howard J. Hamilton
VLDB
2004
ACM
119views Database» more  VLDB 2004»
14 years 4 months ago
Evaluating holistic aggregators efficiently for very large datasets
Indatawarehousingapplications,numerousOLAP queries involve the processing of holistic aggregators such as computing the "top n," median, quantiles, etc. In this paper, we...
Lixin Fu, Sanguthevar Rajasekaran