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ICCV
2009
IEEE
1556views Computer Vision» more  ICCV 2009»
16 years 2 months ago
Kernel Methods for Weakly Supervised Mean Shift Clustering
Mean shift clustering is a powerful unsupervised data analysis technique which does not require prior knowledge of the number of clusters, and does not constrain the shape of th...
Oncel Tuzel, Fatih Porikli, Peter Meer
ICASSP
2009
IEEE
15 years 4 months ago
Exploring functional connectivity in fMRI via clustering
In this paper we investigate the use of data driven clustering methods for functional connectivity analysis in fMRI. In particular, we consider the K-Means and Spectral Clustering...
Archana Venkataraman, Koene R. A. Van Dijk, Randy ...
CGO
2006
IEEE
15 years 3 months ago
Compiler-directed Data Partitioning for Multicluster Processors
Multicluster architectures overcome the scaling problem of centralized resources by distributing the datapath, register file, and memory subsystem across multiple clusters connec...
Michael L. Chu, Scott A. Mahlke
GECCO
2003
Springer
322views Optimization» more  GECCO 2003»
15 years 2 months ago
AntClust: Ant Clustering and Web Usage Mining
Abstract. In this paper, we propose a new ant-based clustering algorithm called AntClust. It is inspired from the chemical recognition system of ants. In this system, the continuou...
Nicolas Labroche, Nicolas Monmarché, Gilles...
IMSCCS
2007
IEEE
15 years 4 months ago
Linear Correlation Analysis of Numeric Attributes for Government Data
To analyze the linear correlations of numeric attributes of government data, this paper proposes a method based on the clustering algorithm. A clustering method is adopted to prun...
Ying Chen, Guochang Gu, Tian-yang Lv, Shaobin Huan...