We examine the use of hidden Markov and hidden semi-Markov models for automatically segmenting an electrocardiogram waveform into its constituent waveform features. An undecimated...
Nicholas P. Hughes, Lionel Tarassenko, Stephen J. ...
Belief propagation on cyclic graphs is an efficient algorithm for computing approximate marginal probability distributions over single nodes and neighboring nodes in the graph. I...
Most proposals for quantum neural networks have skipped over the problem of how to train the networks. The mechanics of quantum computing are different enough from classical compu...
We present a connectionist architecture that can learn a model of the relations between perceptions and actions and use this model for behavior planning. State representations are...
Learning from ambiguous training data is highly relevant in many applications. We present a new learning algorithm for classification problems where labels are associated with se...