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215
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CVPR
2007
IEEE
16 years 9 months ago
Adaptive Distance Metric Learning for Clustering
A good distance metric is crucial for unsupervised learning from high-dimensional data. To learn a metric without any constraint or class label information, most unsupervised metr...
Jieping Ye, Zheng Zhao, Huan Liu
190
Voted
IPPS
2009
IEEE
16 years 1 months ago
Application profiling on Cell-based clusters
In this paper, we present a methodology for profiling parallel applications executing on the IBM PowerXCell 8i (commonly referred to as the “Cell” processor). Specifically, we...
Hikmet Dursun, Kevin J. Barker, Darren J. Kerbyson...
184
Voted
IPPS
2007
IEEE
16 years 1 months ago
Towards A Better Understanding of Workload Dynamics on Data-Intensive Clusters and Grids
This paper presents a comprehensive statistical analysis of workloads collected on data-intensive clusters and Grids. The analysis is conducted at different levels, including Virt...
Hui Li, Lex Wolters
PDP
2005
IEEE
16 years 18 days ago
Memory Bandwidth Aware Scheduling for SMP Cluster Nodes
Clusters of SMPs are becoming increasingly common. However, the shared memory design of SMPs and the consequential contention between system processors for access to main memory c...
Evangelos Koukis, Nectarios Koziris
173
Voted
GECCO
2004
Springer
116views Optimization» more  GECCO 2004»
16 years 12 days ago
Reducing Fitness Evaluations Using Clustering Techniques and Neural Network Ensembles
Abstract. In many real-world applications of evolutionary computation, it is essential to reduce the number of fitness evaluations. To this end, computationally efficient models c...
Yaochu Jin, Bernhard Sendhoff