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IPPS
2010
IEEE
14 years 11 months ago
Improving MapReduce performance through data placement in heterogeneous Hadoop clusters
MapReduce has become an important distributed processing model for large-scale data-intensive applications like data mining and web indexing. Hadoop
Jiong Xie, Shu Yin, Xiaojun Ruan, Zhiyang Ding, Yu...
121
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ICDM
2009
IEEE
172views Data Mining» more  ICDM 2009»
15 years 8 months ago
Sparse Least-Squares Methods in the Parallel Machine Learning (PML) Framework
—We describe parallel methods for solving large-scale, high-dimensional, sparse least-squares problems that arise in machine learning applications such as document classificatio...
Ramesh Natarajan, Vikas Sindhwani, Shirish Tatikon...
ICDCS
2009
IEEE
15 years 10 months ago
CLIQUE: Role-Free Clustering with Q-Learning for Wireless Sensor Networks
Clustering and aggregation inherently increase wireless sensor network (WSN) lifetime by collecting information within a cluster at a cluster head, reducing the amount of data thr...
Anna Förster, Amy L. Murphy
IPPS
2007
IEEE
15 years 7 months ago
A Performance Prediction Framework for Grid-Based Data Mining Applications
For a grid middleware to perform resource allocation, prediction models are needed, which can determine how long an application will take for completion on a particular platform o...
Leonid Glimcher, Gagan Agrawal
ICDCS
2002
IEEE
15 years 6 months ago
A Fully Distributed Framework for Cost-Sensitive Data Mining
Data mining systems aim to discover patterns and extract useful information from facts recorded in databases. A widely adopted approach is to apply machine learning algorithms to ...
Wei Fan, Haixun Wang, Philip S. Yu, Salvatore J. S...