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» Distributed Data Clustering Can Be Efficient and Exact
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183
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DKE
2008
79views more  DKE 2008»
15 years 6 months ago
Extracting k most important groups from data efficiently
We study an important data analysis operator, which extracts the k most important groups from data (i.e., the k groups with the highest aggregate values). In a data warehousing co...
Man Lung Yiu, Nikos Mamoulis, Vagelis Hristidis
HICSS
2005
IEEE
145views Biometrics» more  HICSS 2005»
15 years 11 months ago
Towards a Reliable and Efficient Distributed Storage System
This paper presents RDSS, a Resource Area Network (RAN)-based Distributed Storage System, which is designed for high scalability, long-term reliability, and operational efficiency...
Xiaodong Li, Chang Liu
JCNS
2010
103views more  JCNS 2010»
15 years 28 days ago
Efficient computation of the maximum a posteriori path and parameter estimation in integrate-and-fire and more general state-spa
A number of important data analysis problems in neuroscience can be solved using state-space models. In this article, we describe fast methods for computing the exact maximum a pos...
Shinsuke Koyama, Liam Paninski
BMCBI
2010
151views more  BMCBI 2010»
15 years 6 months ago
Misty Mountain clustering: application to fast unsupervised flow cytometry gating
Background: There are many important clustering questions in computational biology for which no satisfactory method exists. Automated clustering algorithms, when applied to large,...
István P. Sugár, Stuart C. Sealfon
163
Voted
IBPRIA
2007
Springer
15 years 10 months ago
Efficiently Downdating, Composing and Splitting Singular Value Decompositions Preserving the Mean Information
Three methods for the efficient downdating, composition and splitting of low rank singular value decompositions are proposed. They are formulated in a closed form, considering the ...
Javier Melenchón, Elisa Martínez