Graph-based semi-supervised learning has recently emerged as a promising approach to data-sparse learning problems in natural language processing. All graph-based algorithms rely ...
Abstract. We investigate the problem of using function approximation in reinforcement learning where the agent’s policy is represented as a classifier mapping states to actions....
Machine learning techniques such as tree induction have become accepted tools for developing generalisations of large data sets, typically for use with production rule systems in p...
Abstract. This article introduces a technique for improving the efficiency of diagnosis through approximate compilation. We extend the approach of compiling a diagnostic model, as...
Abstract. In the future it is likely that peer communities will be routinely established for the purpose of sharing electronic resources and targeted information among groups of pe...