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STACS
2007
Springer
16 years 1 months 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
BMCBI
2008
132views more  BMCBI 2008»
15 years 7 months ago
Clustering ionic flow blockade toggles with a Mixture of HMMs
Background: Ionic current blockade signal processing, for use in nanopore detection, offers a promising new way to analyze single molecule properties with potential implications f...
Alexander G. Churbanov, Stephen Winters-Hilt
COMGEO
2004
ACM
15 years 7 months ago
A local search approximation algorithm for k-means clustering
In k-means clustering we are given a set of n data points in d-dimensional space d and an integer k, and the problem is to determine a set of k points in d , called centers, to mi...
Tapas Kanungo, David M. Mount, Nathan S. Netanyahu...
CVPR
2007
IEEE
16 years 9 months ago
Segmenting Motions of Different Types by Unsupervised Manifold Clustering
We propose a novel algorithm for segmenting multiple motions of different types from point correspondences in multiple affine or perspective views. Since point trajectories associ...
Alvina Goh, René Vidal
EMNETS
2007
15 years 11 months ago
Image browsing, processing, and clustering for participatory sensing: lessons from a DietSense prototype
Imagers are an increasingly significant source of sensory observations about human activity and the urban environment. ImageScape is a software tool for processing, clustering, an...
Sasank Reddy, Andrew Parker, Josh Hyman, Jeff Burk...