Bayesian classifiers such as Naive Bayes or Tree Augmented Naive Bayes (TAN) have shown excellent performance given their simplicity and heavy underlying independence assumptions....
In the standard feature selection problem, we are given a fixed set of candidate features for use in a learning problem, and must select a subset that will be used to train a mode...
We consider a fundamental problem in computational learning theory: learning an arbitrary Boolean function which depends on an unknown set of k out of n Boolean variables. We give...
Elchanan Mossel, Ryan O'Donnell, Rocco A. Servedio
We present a general approach for designing approximation algorithms for a fundamental class of geometric clustering problems in arbitrary dimensions. More specifically, our appro...
Wenceslas Fernandez de la Vega, Marek Karpinski, C...
We formalize the problem of maintaining time-decaying aggregates and statistics of a data stream: the relative contribution of each data item to the aggregate is scaled down by a ...