Bayesian priors offer a compact yet general means of incorporating domain knowledge into many learning tasks. The correctness of the Bayesian analysis and inference, however, lar...
In this paper, we discuss design considerations and our plans to develop a generalized framework for intelligent support in educational argumentation systems. Our goal is to develo...
Oliver Scheuer, Bruce M. McLaren, Frank Loll, Niel...
Background: We propose a statistically principled baseline correction method, derived from a parametric smoothing model. It uses a score function to describe the key features of b...
We organized a challenge for IJCNN 2007 to assess the added value of prior domain knowledge in machine learning. Most commercial data mining programs accept data pre-formatted in ...
Isabelle Guyon, Amir Saffari, Gideon Dror, Gavin C...
A good architecture is a necessary condition to guarantee that the expected levels of performance, availability, fault tolerance, and scalability are achieved by the implemented s...
Giovanni Bricconi, Emma Tracanella, Elisabetta Di ...