The use of compression algorithms in machine learning tasks such as clustering and classification has appeared in a variety of fields, sometimes with the promise of reducing probl...
Statistical methods for voice conversion are usually based on a single model selected in order to represent a tradeoff between goodness of fit and complexity. In this paper we ass...
Maximum entropy framework proved to be expressive and powerful for the statistical language modelling, but it suffers from the computational expensiveness of the model building. T...
The application of frequent patterns in classification has demonstrated its power in recent studies. It often adopts a two-step approach: frequent pattern (or classification rule) ...
Abstract. Load-Balancing is a significant problem in heterogeneous distributed systems. There exist many load balancing algorithms, however, most approaches are very problem speci...