Abstract. Model transformations operate on models conforming to precisely defined metamodels. Consequently, it often seems relatively easy to chain them: the output of a transforma...
The well-known backpropagation (BP) derivative computation process for multilayer perceptrons (MLP) learning can be viewed as a simplified version of the Kelley-Bryson gradient f...
Abstract Trained musicians intuitively produce expressive variations that add to their audience's enjoyment. However, there is little quantitative information about the kinds ...
We describe a new tagging model where the states of a hidden Markov model (HMM) estimated by unsupervised learning are incorporated as the features in a maximum entropy model. Our...
Robotic controllers take advantage from neural network learning capabilities as long as the dimensionality of the problem is kept moderate. This paper explores the possibilities of...