This paper proposes a neural network model that extracts axes of symmetry from visual patterns. The input patterns can be line drawings, plane figures or gray-scaled natural image...
We present a new approach to bounding the true error rate of a continuous valued classifier based upon PAC-Bayes bounds. The method first constructs a distribution over classifier...
We investigate using gradient descent methods for learning ranking functions; we propose a simple probabilistic cost function, and we introduce RankNet, an implementation of these...
Christopher J. C. Burges, Tal Shaked, Erin Renshaw...
Due to computational intractability, large scale coordination algorithms are necessarily heuristic and hence require tuning for particular environments. In domains where character...
Recent years have seen the discovery of freely diffusing gaseous neurotransmitters, such as nitric oxide (NO), in biological nervous systems. A type of artificial neural network (A...
Andrew Philippides, Phil Husbands, Tom Smith, Mich...