The Bayesian framework of learning from positive noise-free examples derived by Muggleton [12] is extended to learning functional hypotheses from positive examples containing norma...
We develop a Bayesian model of digitized archival films and use this for denoising, or more specifically de-graining, individual frames. In contrast to previous approaches our mod...
Teodor Mihai Moldovan, Stefan Roth, Michael J. Bla...
In this paper we discuss the application of a new machine learning approach - Argument Based Machine Learning - to the legal domain. An experiment using a dataset which has also be...
Martin Mozina, Jure Zabkar, Trevor J. M. Bench-Cap...
The intelligibility of speech in noisy environments depends not only on the functionality of listeners' peripheral auditory systems, but also on cognitive factors such as the...
We present an optimization algorithm that combines active learning and locally-weighted regression to find extreme points of noisy and complex functions. We apply our algorithm to...