To explore the Perturb and Combine idea for estimating probability densities, we study mixtures of tree structured Markov networks derived by bagging combined with the Chow and Liu...
Sourour Ammar, Philippe Leray, Boris Defourny, Lou...
We introduce a boosting framework to solve a classification problem with added manifold and ambient regularization costs. It allows for a natural extension of boosting into both s...
Nicolas Loeff, David A. Forsyth, Deepak Ramachandr...
We study a new placement problem: the reproducing placement problem (RPP). In each phase a module (or gate) is decomposed into two (or more) simpler modules. The goal is nd a \go...
We consider the problem of compressing graphs of the link structure of the World Wide Web. We provide efficient algorithms for such compression that are motivated by recently prop...
Abstract--This paper addresses the challenging problem of finding collision-free trajectories for many robots moving toward individual goals within a common environment. Most popul...