We present a new approach for dealing with distribution change and concept drift when learning from data sequences that may vary with time. We use sliding windows whose size, inst...
The need for network stability and reliability has led to the growth of autonomic networks [2] that can provide more stable and more reliable communications via on-line measuremen...
A conversational method of teaching whereby the students engage each other as a key part of the learning experience achieves a higher percentage of high grades (and presumably bet...
In this paper an omnidirectional Distributed Vision System (DVS) is presented. The presented DVS is able to learn to navigate a mobile robot in its working environment without any...
Emanuele Menegatti, C. Simionato, Stefano Tonello,...
We show how the regularizer of Transductive Support Vector Machines (TSVM) can be trained by stochastic gradient descent for linear models and multi-layer architectures. The resul...
Michael Karlen, Jason Weston, Ayse Erkan, Ronan Co...