Abstract. The original Semantic Web vision was explicit in the need for intelligent autonomous agents that would represent users and help them navigate the Semantic Web. We argue t...
Gunnar Aastrand Grimnes, Peter Edwards, Alun D. Pr...
— This paper addresses the problem of understanding preservation and reconstruction requirements for computeraided medical decision-making. With an increasing number of computer-...
With the proliferation of extremely high-dimensional data, feature selection algorithms have become indispensable components of the learning process. Strangely, despite extensive ...
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
This perspective paper explores principles of unsupervised learning and how they relate to face recognition. Dependency coding and information maximization appear to be central pr...