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» Clustering with the Connectivity Kernel
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ICML
2004
IEEE
14 years 10 months ago
K-means clustering via principal component analysis
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
Chris H. Q. Ding, Xiaofeng He
NPC
2005
Springer
14 years 3 months ago
TCP-ABC: From Multiple TCP Connections to Atomic Broadcasting
In this paper, we proposed a novel scheme, named as TCP-ABC, which replicates the server side TCP connections among multiple server nodes of a cluster. By guaranteeing atomic reque...
Zhiyuan Shao, Hai Jin, Wenbin Jiang, Bin Cheng
ICDM
2006
IEEE
139views Data Mining» more  ICDM 2006»
14 years 3 months ago
Unsupervised Clustering In Streaming Data
Tools for automatically clustering streaming data are becoming increasingly important as data acquisition technology continues to advance. In this paper we present an extension of...
Dimitris K. Tasoulis, Niall M. Adams, David J. Han...
CLUSTER
2003
IEEE
14 years 2 months ago
A Performance Comparison of Linux and a Lightweight Kernel
In this paper, we compare running the Linux operating system on the compute nodes of ASCI Red hardware to running a specialized, highly-optimized lightweight kernel (LWK) operatin...
Ron Brightwell, Rolf Riesen, Keith D. Underwood, T...
ICONIP
2004
13 years 11 months ago
Semi-supervised Kernel-Based Fuzzy C-Means
This paper presents a semi-supervised kernel-based fuzzy c-means algorithm called S2KFCM by introducing semi-supervised learning technique and the kernel method simultaneously into...
Daoqiang Zhang, Keren Tan, Songcan Chen