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» Clustering with Local and Global Regularization
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ITSL
2008
13 years 9 months ago
An Empirical Comparison of NML Clustering Algorithms
Clustering can be defined as a data assignment problem where the goal is to partition the data into nonhierarchical groups of items. In our previous work, we suggested an informati...
Petri Kontkanen, Petri Myllymäki
PLDI
2003
ACM
14 years 29 days ago
Predicting whole-program locality through reuse distance analysis
Profiling can accurately analyze program behavior for select data inputs. We show that profiling can also predict program locality for inputs other than profiled ones. Here loc...
Chen Ding, Yutao Zhong
VEE
2009
ACM
172views Virtualization» more  VEE 2009»
14 years 2 months ago
Entropy: a consolidation manager for clusters
Clusters provide powerful computing environments, but in practice much of this power goes to waste, due to the static allocation of tasks to nodes, regardless of their changing co...
Fabien Hermenier, Xavier Lorca, Jean-Marc Menaud, ...
MICRO
2010
IEEE
153views Hardware» more  MICRO 2010»
13 years 5 months ago
Scalable Speculative Parallelization on Commodity Clusters
While clusters of commodity servers and switches are the most popular form of large-scale parallel computers, many programs are not easily parallelized for execution upon them. In...
Hanjun Kim, Arun Raman, Feng Liu, Jae W. Lee, Davi...
AAAI
2008
13 years 10 months ago
Clustering via Random Walk Hitting Time on Directed Graphs
In this paper, we present a general data clustering algorithm which is based on the asymmetric pairwise measure of Markov random walk hitting time on directed graphs. Unlike tradi...
Mo Chen, Jianzhuang Liu, Xiaoou Tang