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» Hierarchical Clustering of a Mixture Model
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ICASSP
2011
IEEE
12 years 11 months ago
Bayesian Compressive Sensing for clustered sparse signals
In traditional framework of Compressive Sensing (CS), only sparse prior on the property of signals in time or frequency domain is adopted to guarantee the exact inverse recovery. ...
Lei Yu, Hong Sun, Jean-Pierre Barbot, Gang Zheng
IJCV
2008
172views more  IJCV 2008»
13 years 7 months ago
Nonparametric Bayesian Image Segmentation
Image segmentation algorithms partition the set of pixels of an image into a specific number of different, spatially homogeneous groups. We propose a nonparametric Bayesian model f...
Peter Orbanz, Joachim M. Buhmann
PR
2007
107views more  PR 2007»
13 years 7 months ago
Newtonian clustering: An approach based on molecular dynamics and global optimization
Given a data set, a dynamical procedure is applied to the data points in order to shrink and separate, possibly overlapping clusters. Namely, Newton’s equations of motion are em...
Konstantinos Blekas, Isaac E. Lagaris
BMCBI
2007
149views more  BMCBI 2007»
13 years 8 months ago
Novel and simple transformation algorithm for combining microarray data sets
Background: With microarray technology, variability in experimental environments such as RNA sources, microarray production, or the use of different platforms, can cause bias. Suc...
Ki-Yeol Kim, Dong Hyuk Ki, Ha Jin Jeong, Hei-Cheul...
SDM
2007
SIAM
184views Data Mining» more  SDM 2007»
13 years 9 months ago
Mining Naturally Smooth Evolution of Clusters from Dynamic Data
Many clustering algorithms have been proposed to partition a set of static data points into groups. In this paper, we consider an evolutionary clustering problem where the input d...
Yi Wang, Shi-Xia Liu, Jianhua Feng, Lizhu Zhou