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» A Large Scale Clustering Scheme for Kernel K-Means
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KDD
2004
ACM
190views Data Mining» more  KDD 2004»
14 years 6 months ago
Kernel k-means: spectral clustering and normalized cuts
Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. Despite significant research, these methods have re...
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
INFOCOM
2005
IEEE
13 years 11 months ago
Network coding for large scale content distribution
— We propose a new scheme for content distribution of large files that is based on network coding. With network coding, each node of the distribution network is able to generate...
Christos Gkantsidis, Pablo Rodriguez
IPPS
2007
IEEE
14 years 2 days ago
An Energy-Efficient Framework for Large-Scale Parallel Storage Systems
Huge energy consumption has become a critical bottleneck for further applying large-scale cluster systems to build new data centers. Among various components of a data center, sto...
Ziliang Zong, Matt Briggs, Nick O'Connor, Xiao Qin
CLUSTER
2008
IEEE
14 years 7 days ago
DLM: A distributed Large Memory System using remote memory swapping over cluster nodes
Abstract—Emerging 64bitOS’s supply a huge amount of memory address space that is essential for new applications using very large data. It is expected that the memory in connect...
Hiroko Midorikawa, Motoyoshi Kurokawa, Ryutaro Him...
HPCA
2001
IEEE
14 years 6 months ago
A New Scalable Directory Architecture for Large-Scale Multiprocessors
The memory overhead introduced by directories constitutes a major hurdle in the scalability of cc-NUMA architectures, which makes the shared-memory paradigm unfeasible for very la...
Manuel E. Acacio, José González, Jos...