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KDD
2003
ACM
180views Data Mining» more  KDD 2003»
16 years 4 months ago
Classifying large data sets using SVMs with hierarchical clusters
Support vector machines (SVMs) have been promising methods for classification and regression analysis because of their solid mathematical foundations which convey several salient ...
Hwanjo Yu, Jiong Yang, Jiawei Han
ACMSE
2007
ACM
15 years 8 months ago
Verifying design modularity, hierarchy, and interaction locality using data clustering techniques
Modularity, hierarchy, and interaction locality are general approaches to reducing the complexity of any large system. A widely used principle in achieving these goals in designin...
Liguo Yu, Srini Ramaswamy
ALGORITHMICA
2006
86views more  ALGORITHMICA 2006»
15 years 4 months ago
Slabpose Columnsort: A New Oblivious Algorithm for Out-of-Core Sorting on Distributed-Memory Clusters
Our goal is to develop a robust out-of-core sorting program for a distributed-memory cluster. The literature contains two dominant paradigms for out-of-core sorting algorithms: me...
Geeta Chaudhry, Thomas H. Cormen
ALMOB
2006
89views more  ALMOB 2006»
15 years 4 months ago
On the maximal cliques in c-max-tolerance graphs and their application in clustering molecular sequences
Given a set S of n locally aligned sequences, it is a needed prerequisite to partition it into groups of very similar sequences to facilitate subsequent computations, such as the ...
Katharina Anna Lehmann, Michael Kaufmann, Stephan ...
TALG
2010
158views more  TALG 2010»
14 years 11 months ago
Clustering for metric and nonmetric distance measures
We study a generalization of the k-median problem with respect to an arbitrary dissimilarity measure D. Given a finite set P of size n, our goal is to find a set C of size k such t...
Marcel R. Ackermann, Johannes Blömer, Christi...