We review a multiple kernel learning (MKL) technique called p regularised multiple kernel Fisher discriminant analysis (MK-FDA), and investigate the effect of feature space denois...
We provide a general framework for learning precise, compact, and fast representations of the Bayesian predictive distribution for a model. This framework is based on minimizing t...
The application of kernel-based learning algorithms has, so far, largely been confined to realvalued data and a few special data types, such as strings. In this paper we propose a...
Collaboration has long been considered an effective approach to learning. However, forming optimal groups can be a time consuming and complex task. Different approaches have been ...
This paper describes the design of a metadata model for capturing presentations developed as part of the VACE project (Video and Audio Capturing and Embedding). VACE is a modular,...