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» Scaling Clustering Algorithms to Large Databases
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SIAMSC
2008
182views more  SIAMSC 2008»
13 years 8 months ago
A Distributed SDP Approach for Large-Scale Noisy Anchor-Free Graph Realization with Applications to Molecular Conformation
We propose a distributed algorithm for solving Euclidean metric realization problems arising from large 3D graphs, using only noisy distance information, and without any prior kno...
Pratik Biswas, Kim-Chuan Toh, Yinyu Ye
BTW
2007
Springer
140views Database» more  BTW 2007»
14 years 2 months ago
SmurfPDMS: A Platform for Query Processing in Large-Scale PDMS
: As Peer Data Management Systems (PDMS) are a focus of current research, there are lots of approaches like query processing or routing issues that have to be evaluated. Since ther...
Katja Hose, Christian Lemke, Jana Quasebarth, Kai-...
ICPPW
2009
IEEE
13 years 6 months ago
A Scalable Parallel Approach for Peptide Identification from Large-Scale Mass Spectrometry Data
Identifying peptides, which are short polymeric chains of amino acid residues in a protein sequence, is of fundamental importance in systems biology research. The most popular appr...
Gaurav Ramesh Kulkarni, Ananth Kalyanaraman, Willi...
SBACPAD
2003
IEEE
180views Hardware» more  SBACPAD 2003»
14 years 1 months ago
New Parallel Algorithms for Frequent Itemset Mining in Very Large Databases
Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
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