The problem of simultaneous feature extraction and selection, for classifier design, is considered. A new framework is proposed, based on boosting algorithms that can either 1) s...
In view of the substantial number of existing feature selection algorithms, the need arises to count on criteria that enables to adequately decide which algorithm to use in certai...
On-Line Analytical Processing (OLAP) based on a dimensional view of data is being used increasingly for the purpose of analyzing very large amounts of data. To improve query perfo...
Torben Bach Pedersen, Christian S. Jensen, Curtis ...
We study the problem of selecting a subset of k random variables from a large set, in order to obtain the best linear prediction of another variable of interest. This problem can ...
Users often need to optimize the selection of objects by appropriately weighting the importance of multiple object attributes. Such optimization problems appear often in operation...
Vagelis Hristidis, Nick Koudas, Yannis Papakonstan...