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» Scaling Clustering Algorithms to Large Databases
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ICDE
2011
IEEE
258views Database» more  ICDE 2011»
14 years 5 months ago
SystemML: Declarative machine learning on MapReduce
Abstract—MapReduce is emerging as a generic parallel programming paradigm for large clusters of machines. This trend combined with the growing need to run machine learning (ML) a...
Amol Ghoting, Rajasekar Krishnamurthy, Edwin P. D....
IJCNN
2008
IEEE
15 years 8 months ago
Two-level clustering approach to training data instance selection: A case study for the steel industry
— Nowadays, huge amounts of information from different industrial processes are stored into databases and companies can improve their production efficiency by mining some new kn...
Heli Koskimäki, Ilmari Juutilainen, Perttu La...
NDSS
2009
IEEE
15 years 8 months ago
Scalable, Behavior-Based Malware Clustering
Anti-malware companies receive thousands of malware samples every day. To process this large quantity, a number of automated analysis tools were developed. These tools execute a m...
Ulrich Bayer, Paolo Milani Comparetti, Clemens Hla...
ICDE
2007
IEEE
211views Database» more  ICDE 2007»
15 years 8 months ago
Document Representation and Dimension Reduction for Text Clustering
Increasingly large text datasets and the high dimensionality associated with natural language create a great challenge in text mining. In this research, a systematic study is cond...
M. Mahdi Shafiei, Singer Wang, Roger Zhang, Evange...
DATE
2009
IEEE
171views Hardware» more  DATE 2009»
15 years 5 months ago
Physically clustered forward body biasing for variability compensation in nanometer CMOS design
Nanometer CMOS scaling has resulted in greatly increased circuit variability, with extremely adverse consequences on design predictability and yield. A number of recent works have...
Ashoka Visweswara Sathanur, Antonio Pullini, Luca ...