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» From Comparing Clusterings to Combining Clusterings
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IPPS
2005
IEEE
14 years 2 months ago
Exploring the Energy-Time Tradeoff in MPI Programs on a Power-Scalable Cluster
Recently, energy has become an important issue in highperformance computing. For example, supercomputers that have energy in mind, such as BlueGene/L, have been built; the idea is...
Vincent W. Freeh, Feng Pan, Nandini Kappiah, David...
CIARP
2005
Springer
14 years 2 months ago
Dynamic Hierarchical Compact Clustering Algorithm
Abstract. In this paper we introduce a general framework for hierarchical clustering that deals with both static and dynamic data sets. From this framework, different hierarchical...
Reynaldo Gil-García, José Manuel Bad...
GECCO
2005
Springer
146views Optimization» more  GECCO 2005»
14 years 2 months ago
An empirical study of the robustness of two module clustering fitness functions
Two of the attractions of search-based software engineering (SBSE) derive from the nature of the fitness functions used to guide the search. These have proved to be highly robust...
Mark Harman, Stephen Swift, Kiarash Mahdavi
SDM
2007
SIAM
176views Data Mining» more  SDM 2007»
13 years 10 months ago
Adaptive Concept Learning through Clustering and Aggregation of Relational Data
We introduce a new approach for Clustering and Aggregating Relational Data (CARD). We assume that data is available in a relational form, where we only have information about the ...
Hichem Frigui, Cheul Hwang
EMNLP
2010
13 years 7 months ago
Clustering-Based Stratified Seed Sampling for Semi-Supervised Relation Classification
Seed sampling is critical in semi-supervised learning. This paper proposes a clusteringbased stratified seed sampling approach to semi-supervised learning. First, various clusteri...
Longhua Qian, Guodong Zhou