This paper addresses the supervised learning in which the class membership of training data are subject to uncertainty. This problem is tackled in the framework of the Dempster-Sha...
This paper proposes a multiclassification algorithm using multilayer perceptron neural network models. It tries to boost two conflicting main objectives of multiclassifiers: a high...
The Intelligent Systems Division of the National Institute of Standards and Technology has been engaged for several years in developing real-time systems for autonomous driving. A...
The 1R procedure for machine learning is a very simple one that proves surprisingly effective on the standard datasets commonly used for evaluation. This paper describes the metho...
Craig G. Nevill-Manning, Geoffrey Holmes, Ian H. W...
Previous work in knowledge transfer in machine learning has been restricted to tasks in a single domain. However, evidence from psychology and neuroscience suggests that humans ar...