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STACS
2007
Springer
16 years 15 days ago
Small Space Representations for Metric Min-Sum k -Clustering and Their Applications
The min-sum k-clustering problem is to partition a metric space (P, d) into k clusters C1, . . . , Ck ⊆ P such that k i=1 p,q∈Ci d(p, q) is minimized. We show the first effi...
Artur Czumaj, Christian Sohler
TCS
2010
15 years 4 months ago
Clustering with partial information
The Correlation Clustering problem, also known as the Cluster Editing problem, seeks to edit a given graph by adding and deleting edges to obtain a collection of disconnected cliq...
Hans L. Bodlaender, Michael R. Fellows, Pinar Hegg...
ICML
2005
IEEE
16 years 7 months ago
A model for handling approximate, noisy or incomplete labeling in text classification
We introduce a Bayesian model, BayesANIL, that is capable of estimating uncertainties associated with the labeling process. Given a labeled or partially labeled training corpus of...
Ganesh Ramakrishnan, Krishna Prasad Chitrapura, Ra...
PODS
2006
ACM
134views Database» more  PODS 2006»
16 years 6 months ago
Approximate quantiles and the order of the stream
Recently, there has been an increased focus on modeling uncertainty by distributions. Suppose we wish to compute a function of a stream whose elements are samples drawn independen...
Sudipto Guha, Andrew McGregor
ISAAC
2009
Springer
127views Algorithms» more  ISAAC 2009»
16 years 29 days ago
Maximal Strip Recovery Problem with Gaps: Hardness and Approximation Algorithms
Abstract. Given two comparative maps, that is two sequences of markers each representing a genome, the Maximal Strip Recovery problem (MSR) asks to extract a largest sequence of ma...
Laurent Bulteau, Guillaume Fertin, Irena Rusu