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» Optimized data fusion for K-means Laplacian clustering
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CDC
2010
IEEE
107views Control Systems» more  CDC 2010»
13 years 9 days ago
Deployment of an unreliable robotic sensor network for spatial estimation
This paper studies an optimal deployment problem for a network of robotic sensors moving in the real line. Given a spatial process of interest, each individual sensor sends a pack...
Jorge Cortes
BMCBI
2010
182views more  BMCBI 2010»
13 years 5 months ago
L2-norm multiple kernel learning and its application to biomedical data fusion
Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...
Shi Yu, Tillmann Falck, Anneleen Daemen, Lé...
ERCIMDL
2000
Springer
147views Education» more  ERCIMDL 2000»
13 years 9 months ago
Map Segmentation by Colour Cube Genetic K-Mean Clustering
Segmentation of a colour image composed of different kinds of texture regions can be a hard problem, namely to compute for an exact texture fields and a decision of the optimum num...
Vitorino Ramos, Fernando Muge
CSB
2005
IEEE
115views Bioinformatics» more  CSB 2005»
13 years 11 months ago
A New Clustering Strategy with Stochastic Merging and Removing Based on Kernel Functions
With hierarchical clustering methods, divisions or fusions, once made, are irrevocable. As a result, when two elements in a bottom-up algorithm are assigned to one cluster, they c...
Huimin Geng, Hesham H. Ali
INFOCOM
2006
IEEE
13 years 11 months ago
Optimal Distributed Detection in Clustered Wireless Sensor Networks: The Weighted Median
− In a clustered, multi-hop sensor network, a large number of inexpensive, geographically-distributed sensor nodes each use their observations of the environment to make local ha...
Qingjiang Tian, Edward J. Coyle