If appropriately used, prior knowledge can significantly improve the predictive accuracy of learning algorithms or reduce the amount of training data needed. In this paper we intr...
Prior knowledge, in the form of simple advice rules, can greatly speed up convergence in learning algorithms. Online learning methods predict the label of the current point and the...
Gautam Kunapuli, Kristin P. Bennett, Amina Shabbee...
The kernel Perceptron is an appealing online learning algorithm that has a drawback: whenever it makes an error it must increase its support set, which slows training and testing ...
In this paper we present a new scheme for detection and tracking of specific objects in a knowledge-based framework. The scheme uses a supervised learning method: Support Vector M...
Lionel Carminati, Jenny Benois-Pineau, Christian J...
This work deals with the application of kernel methods to structured relational settings such as semantic knowledge bases expressed in Description Logics. Our method integrates a n...