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» Computing LTS Regression for Large Data Sets
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PVLDB
2008
182views more  PVLDB 2008»
13 years 7 months ago
SCOPE: easy and efficient parallel processing of massive data sets
Companies providing cloud-scale services have an increasing need to store and analyze massive data sets such as search logs and click streams. For cost and performance reasons, pr...
Ronnie Chaiken, Bob Jenkins, Per-Åke Larson,...
ICAC
2009
IEEE
14 years 2 months ago
Ranking the importance of alerts for problem determination in large computer systems
The complexity of large computer systems has raised unprecedented challenges for system management. In practice, operators often collect large volume of monitoring data from system...
Guofei Jiang, Haifeng Chen, Kenji Yoshihira, Akhil...
VIS
2004
IEEE
145views Visualization» more  VIS 2004»
14 years 9 months ago
Compression, Segmentation, and Modeling of Large-Scale Filamentary Volumetric Data
We describe a method for processing large amounts of volumetric data collected from a Knife Edge Scanning Microscope (KESM). The neuronal data that we acquire consists of thin, br...
Bruce H. McCormick, David Mayerich, John Keyser, P...
KDD
2008
ACM
135views Data Mining» more  KDD 2008»
14 years 8 months ago
Effective and efficient itemset pattern summarization: regression-based approaches
In this paper, we propose a set of novel regression-based approaches to effectively and efficiently summarize frequent itemset patterns. Specifically, we show that the problem of ...
Ruoming Jin, Muad Abu-Ata, Yang Xiang, Ning Ruan
ICPP
2000
IEEE
14 years 7 days ago
A Scalable Parallel Subspace Clustering Algorithm for Massive Data Sets
Clustering is a data mining problem which finds dense regions in a sparse multi-dimensional data set. The attribute values and ranges of these regions characterize the clusters. ...
Harsha S. Nagesh, Sanjay Goil, Alok N. Choudhary