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PAMI
2008
162views more  PAMI 2008»
13 years 7 months ago
Dimensionality Reduction of Clustered Data Sets
We present a novel probabilistic latent variable model to perform linear dimensionality reduction on data sets which contain clusters. We prove that the maximum likelihood solution...
Guido Sanguinetti
ISBRA
2007
Springer
14 years 2 months ago
Clustering Algorithms Optimizer: A Framework for Large Datasets
Clustering algorithms are employed in many bioinformatics tasks, including categorization of protein sequences and analysis of gene-expression data. Although these algorithms are r...
Roy Varshavsky, David Horn, Michal Linial
KDD
2009
ACM
140views Data Mining» more  KDD 2009»
14 years 8 months ago
Improving clustering stability with combinatorial MRFs
: ? Improving Clustering Stability with Combinatorial MRFs Bekkerman, Ron; Scholz, Martin; Viswanathan, Krishnamurthy HP Laboratories HPL-2009-46 Clustering stability, combinatoria...
Ron Bekkerman, Martin Scholz, Krishnamurthy Viswan...
STOC
2003
ACM
141views Algorithms» more  STOC 2003»
14 years 8 months ago
Better streaming algorithms for clustering problems
We study clustering problems in the streaming model, where the goal is to cluster a set of points by making one pass (or a few passes) over the data using a small amount of storag...
Moses Charikar, Liadan O'Callaghan, Rina Panigrahy
IDA
2009
Springer
14 years 2 months ago
How to Control Clustering Results? Flexible Clustering Aggregation
One of the most important and challenging questions in the area of clustering is how to choose the best-fitting algorithm and parameterization to obtain an optiml clustering for t...
Martin Hahmann, Peter Benjamin Volk, Frank Rosenth...