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132
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ISAAC
2009
Springer
175views Algorithms» more  ISAAC 2009»
15 years 10 months ago
Worst-Case and Smoothed Analysis of k-Means Clustering with Bregman Divergences
The k-means algorithm is the method of choice for clustering large-scale data sets and it performs exceedingly well in practice. Most of the theoretical work is restricted to the c...
Bodo Manthey, Heiko Röglin
105
Voted
CF
2004
ACM
15 years 9 months ago
An information-interconnectivity-based retrieval method for network attached storage
Network attached disk storage is characterized by independent network attachment and embedded intelligence. For Internet applications, it provides the key functionality of geograp...
Iliyak Georgiev, Ivo I. Georgiev
123
Voted
ICPR
2006
IEEE
16 years 4 months ago
Graph Matching using Commute Time Spanning Trees
This paper exploits the properties of the commute time for the purposes of graph matching. Our starting point is the random walk on the graph, which is determined by the heat-kern...
Edwin R. Hancock, Huaijun Qiu
112
Voted
CLUSTER
2004
IEEE
15 years 7 months ago
XChange: coupling parallel applications in a dynamic environment
Modern computational science applications are becoming increasingly multi-disciplinaty involving widely distributed research teams and their underlying computational platforms. A ...
Hasan Abbasi, Matthew Wolf, Karsten Schwan, Greg E...
139
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INFOCOM
2006
IEEE
15 years 9 months ago
Scalable Clustering of Internet Paths by Shared Congestion
— Internet paths sharing the same bottleneck can be identified using several shared congestion detection techniques. However, all of these techniques have been designed to detec...
Min Sik Kim, Taekhyun Kim, YongJune Shin, Simon S....