Label ranking studies the problem of learning a mapping from instances to rankings over a predefined set of labels. We approach this setting from a case-based perspective and propo...
Abstract— We present a learning-based approach for longrange vision that is able to accurately classify complex terrain at distances up to the horizon, thus allowing high-level s...
Raia Hadsell, Ayse Erkan, Pierre Sermanet, Marco S...
Despite the tremendous progress in robotic hardware and in both sensorial and computing efficiencies the performance of contemporary autonomous robots is still far below that of ...
The World Wide Web has transformed itself in the last few years from a simple state-less multimedia platform to a global distributed processing environment. As Web computing gains...
We apply robust Bayesian decision theory to improve both generative and discriminative learners under bias in class proportions in labeled training data, when the true class propo...