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» Constraint Programming for Data Mining and Machine Learning
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SDM
2012
SIAM
237views Data Mining» more  SDM 2012»
13 years 4 months ago
A Distributed Kernel Summation Framework for General-Dimension Machine Learning
Kernel summations are a ubiquitous key computational bottleneck in many data analysis methods. In this paper, we attempt to marry, for the first time, the best relevant technique...
Dongryeol Lee, Richard W. Vuduc, Alexander G. Gray
110
Voted
SIGKDD
2000
237views more  SIGKDD 2000»
15 years 1 months ago
The UCI KDD Archive of Large Data Sets for Data Mining Research and Experimentation
Advances in data collection and storage have allowed organizations to create massive, complex and heterogeneous databases, which have stymied traditional methods of data analysis....
Stephen D. Bay, Dennis F. Kibler, Michael J. Pazza...
86
Voted
ICASSP
2008
IEEE
15 years 8 months ago
Nested support vector machines
The one-class and cost-sensitive support vector machines (SVMs) are state-of-the-art machine learning methods for estimating density level sets and solving weighted classificatio...
Gyemin Lee, Clayton Scott
IUI
2000
ACM
15 years 6 months ago
APE: learning user's habits to automate repetitive tasks
The APE (Adaptive Programming Environment) project focuses on applying Machine Learning techniques to embed a software assistant into the VisualWorks Smalltalk interactive program...
Jean-David Ruvini, Christophe Dony
KDD
2007
ACM
210views Data Mining» more  KDD 2007»
15 years 8 months ago
Machine learning for stock selection
In this paper, we propose a new method called Prototype Ranking (PR) designed for the stock selection problem. PR takes into account the huge size of real-world stock data and app...
Robert J. Yan, Charles X. Ling