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» Clustering with or without the Approximation
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CVPR
2007
IEEE
16 years 8 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
OSDI
2004
ACM
16 years 6 months ago
MapReduce: Simplified Data Processing on Large Clusters
MapReduce is a programming model and an associated implementation for processing and generating large data sets. Users specify a map function that processes a key/value pair to ge...
Jeffrey Dean, Sanjay Ghemawat
ICDM
2007
IEEE
129views Data Mining» more  ICDM 2007»
16 years 25 days ago
Semi-supervised Clustering Using Bayesian Regularization
Text clustering is most commonly treated as a fully automated task without user supervision. However, we can improve clustering performance using supervision in the form of pairwi...
Zuobing Xu, Ram Akella, Mike Ching, Renjie Tang
ICPP
2007
IEEE
16 years 24 days ago
CPU MISER: A Performance-Directed, Run-Time System for Power-Aware Clusters
Performance and power are critical design constraints in today’s high-end computing systems. Reducing power consumption without impacting system performance is a challenge for t...
Rong Ge, Xizhou Feng, Wu-chun Feng, Kirk W. Camero...
ICPADS
2006
IEEE
16 years 16 days ago
Memory and Network Bandwidth Aware Scheduling of Multiprogrammed Workloads on Clusters of SMPs
Symmetric Multiprocessors (SMPs), combined with modern interconnection technologies are commonly used to build cost-effective compute clusters. However, contention among processor...
Evangelos Koukis, Nectarios Koziris