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» Approximation algorithms for clustering uncertain data
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SIGMOD
2006
ACM
111views Database» more  SIGMOD 2006»
14 years 7 months ago
Reconciling while tolerating disagreement in collaborative data sharing
In many data sharing settings, such as within the biological and biomedical communities, global data consistency is not always attainable: different sites' data may be dirty,...
Nicholas E. Taylor, Zachary G. Ives
ICML
2005
IEEE
14 years 8 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
CVPR
2005
IEEE
14 years 9 months ago
A Bayesian Approach to Unsupervised Feature Selection and Density Estimation Using Expectation Propagation
We propose an approximate Bayesian approach for unsupervised feature selection and density estimation, where the importance of the features for clustering is used as the measure f...
Shaorong Chang, Nilanjan Dasgupta, Lawrence Carin
COLT
2003
Springer
14 years 26 days ago
On Finding Large Conjunctive Clusters
We propose a new formulation of the clustering problem that differs from previous work in several aspects. First, the goal is to explicitly output a collection of simple and meani...
Nina Mishra, Dana Ron, Ram Swaminathan
ALMOB
2006
109views more  ALMOB 2006»
13 years 7 months ago
A novel functional module detection algorithm for protein-protein interaction networks
Background: The sparse connectivity of protein-protein interaction data sets makes identification of functional modules challenging. The purpose of this study is to critically eva...
Woochang Hwang, Young-Rae Cho, Aidong Zhang, Mural...