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KDD
2001
ACM
166views Data Mining» more  KDD 2001»
16 years 7 months ago
Generalized clustering, supervised learning, and data assignment
Clustering algorithms have become increasingly important in handling and analyzing data. Considerable work has been done in devising effective but increasingly specific clustering...
Annaka Kalton, Pat Langley, Kiri Wagstaff, Jungsoo...
DATAMINE
2006
157views more  DATAMINE 2006»
15 years 6 months ago
Data Clustering with Partial Supervision
Clustering with partial supervision finds its application in situations where data is neither entirely nor accurately labeled. This paper discusses a semisupervised clustering algo...
Abdelhamid Bouchachia, Witold Pedrycz
HPDC
2002
IEEE
15 years 11 months ago
Decoupling Computation and Data Scheduling in Distributed Data-Intensive Applications
In high energy physics, bioinformatics, and other disciplines, we encounter applications involving numerous, loosely coupled jobs that both access and generate large data sets. So...
Kavitha Ranganathan, Ian T. Foster
MDAI
2009
Springer
15 years 11 months ago
Comparison of Data Structures for Computing Formal Concepts
Presented is preliminary study of the role of data structures in algorithms for formal concept analysis. Studied is performance of selected algorithms in dependence on chosen data ...
Petr Krajca, Vilém Vychodil
DIS
2006
Springer
15 years 10 months ago
Clustering Pairwise Distances with Missing Data: Maximum Cuts Versus Normalized Cuts
Abstract. Clustering algorithms based on a matrix of pairwise similarities (kernel matrix) for the data are widely known and used, a particularly popular class being spectral clust...
Jan Poland, Thomas Zeugmann