We present a new family of subgradient methods that dynamically incorporate knowledge of the geometry of the data observed in earlier iterations to perform more informative gradie...
Over the last 20 years there has been increasing interest in work-based learning in the UK business sector as a means to improve and increase the skills of the UK workforce. The m...
In recent years there have been efforts to develop a probabilistic framework to explain the workings of a Learning Classifier System. This direction of research has met with lim...
There is a strong technological and economic push for higher education providers to adopt online learning strategies. This is driven, in part, by the requirement of industry for l...
In this paper we propose a Gaussian-kernel-based online kernel density estimation which can be used for applications of online probability density estimation and online learning. ...