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ALGORITHMICA
2006
74views more  ALGORITHMICA 2006»
13 years 8 months ago
Parallelizing Feature Selection
Classification is a key problem in machine learning/data mining. Algorithms for classification have the ability to predict the class of a new instance after having been trained on...
Jerffeson Teixeira de Souza, Stan Matwin, Nathalie...
ICNC
2005
Springer
14 years 1 months ago
Training Data Selection for Support Vector Machines
Abstract. In recent years, support vector machines (SVMs) have become a popular tool for pattern recognition and machine learning. Training a SVM involves solving a constrained qua...
Jigang Wang, Predrag Neskovic, Leon N. Cooper
IPPS
2002
IEEE
14 years 29 days ago
Parallel Incremental 2D-Discretization on Dynamic Datasets
Most current work in data mining assumes that the database is static, and a database update requires rediscovering all the patterns by scanning the entire old and new database. Su...
Srinivasan Parthasarathy, Arun Ramakrishnan
CORR
2008
Springer
113views Education» more  CORR 2008»
13 years 8 months ago
Robustness, Risk, and Regularization in Support Vector Machines
We consider two new formulations for classification problems in the spirit of support vector machines based on robust optimization. Our formulations are designed to build in prote...
Huan Xu, Shie Mannor, Constantine Caramanis
SPAA
1997
ACM
14 years 6 days ago
A Localized Algorithm for Parallel Association Mining
Discovery of association rules is an important database mining problem. Mining for association rules involves extracting patterns from large databases and inferring useful rules f...
Mohammed Javeed Zaki, Srinivasan Parthasarathy, We...