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TKDE
2012
270views Formal Methods» more  TKDE 2012»
13 years 3 months ago
Low-Rank Kernel Matrix Factorization for Large-Scale Evolutionary Clustering
—Traditional clustering techniques are inapplicable to problems where the relationships between data points evolve over time. Not only is it important for the clustering algorith...
Lijun Wang, Manjeet Rege, Ming Dong, Yongsheng Din...
FOCS
2003
IEEE
15 years 6 months ago
Clustering with Qualitative Information
We consider the problem of clustering a collection of elements based on pairwise judgments of similarity and dissimilarity. Bansal, Blum and Chawla (in: Proceedings of 43rd FOCS, ...
Moses Charikar, Venkatesan Guruswami, Anthony Wirt...
82
Voted
BIOINFORMATICS
2006
85views more  BIOINFORMATICS 2006»
15 years 24 days ago
Clusterv: a tool for assessing the reliability of clusters discovered in DNA microarray data
Summary: We present a new R package for the assessment of the reliability of clusters discovered in high dimensional DNA microarray data. The package implements methods based on r...
Giorgio Valentini
117
Voted
ICML
2005
IEEE
16 years 1 months ago
Bayesian hierarchical clustering
We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages ove...
Katherine A. Heller, Zoubin Ghahramani
81
Voted
NIPS
2007
15 years 2 months ago
Convex Clustering with Exemplar-Based Models
Clustering is often formulated as the maximum likelihood estimation of a mixture model that explains the data. The EM algorithm widely used to solve the resulting optimization pro...
Danial Lashkari, Polina Golland