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KDD
2004
ACM
624views Data Mining» more  KDD 2004»
15 years 9 months ago
Programming the K-means clustering algorithm in SQL
Using SQL has not been considered an efficient and feasible way to implement data mining algorithms. Although this is true for many data mining, machine learning and statistical a...
Carlos Ordonez
SSPR
2004
Springer
15 years 9 months ago
Clustering Variable Length Sequences by Eigenvector Decomposition Using HMM
We present a novel clustering method using HMM parameter space and eigenvector decomposition. Unlike the existing methods, our algorithm can cluster both constant and variable leng...
Fatih Murat Porikli
CVPR
2008
IEEE
16 years 6 months ago
Simultaneous clustering and tracking unknown number of objects
In this paper, we present a novel on-line probabilistic generative model that simultaneously deals with both the clustering and the tracking of an unknown number of moving objects...
Katsuhiko Ishiguro, Takeshi Yamada, Naonori Ueda
ICPR
2008
IEEE
15 years 10 months ago
A clustering algorithm combine the FCM algorithm with supervised learning normal mixture model
In this paper we propose a new clustering algorithm which combines the FCM clustering algorithm with the supervised learning normal mixture model; we call the algorithm as the FCM...
Wei Wang, Chunheng Wang, Xia Cui, Ai Wang
CCGRID
2007
IEEE
15 years 10 months ago
Virtual Clusters on the Fly - Fast, Scalable, and Flexible Installation
One of the advantages in virtualized computing clusters compared to traditional shared HPC environments is their ability to accommodate user-specific system customization. Howeve...
Hideo Nishimura, Naoya Maruyama, Satoshi Matsuoka