We report the results of fitting mixture models to the distribution of expression values for individual genes over a broad range of normal tissues, which we call the marginal expr...
This paper describes a pattern classification approach for detecting frontal-view faces via learning a decision boundary. The classification can be achieved either by explicit est...
Abstract. We describe and analyze an algorithm for predicting a sequence of n-dimensional binary vectors based on a set of experts making vector predictions in [0, 1]n . We measure...
Matthew Henderson, John Shawe-Taylor, Janez Zerovn...
Unsupervised or Self-Organized learning algorithms have become very popular for discovery of significant patterns or features in the input data. The three prominent algorithms name...
Abstract. This paper proposes a new learning method for process neural networks (PNNs) based on the Gaussian mixture functions and particle swarm optimization (PSO), called PSO-LM....