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
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...
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...
The APE (Adaptive Programming Environment) project focuses on applying Machine Learning techniques to embed a software assistant into the VisualWorks Smalltalk interactive program...
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...