Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...
Long Han, Mark J. Embrechts, Boleslaw K. Szymanski...
— In this paper, we lay the groundwork for extending our previously developed ASyMTRe architecture to enable constructivist learning for multi-robot team tasks. The ASyMTRe archi...
Ad-hoc networks of mobile devices such as smart phones and PDAs represent a new and exciting distributed system architecture. Building distributed applications on such an architec...
Yang Ni, Ulrich Kremer, Adrian Stere, Liviu Iftode
We study an extension of the "standard" learning models to settings where observing the value of an attribute has an associated cost (which might be different for differ...
This paper studies a novel paradigm for learning formal languages from positive and negative examples which consists of mapping strings to an appropriate highdimensional feature s...