Decision tree induction techniques attempt to find small trees that fit a training set of data. This preference for smaller trees, which provides a learning bias, is often justifie...
Christian Bessiere, Emmanuel Hebrard, Barry O'Sull...
This paper describes a technique for learning both the number of states and the topologyof Hidden Markov Models from examples. The inductionprocess starts with the most specific m...
This paper presents a corpus-based algorithm capable of inducing inflectional morphological analyses of both regular and highly irregular forms (such as broughtbring) from distrib...
The performance of multiuser detection (MUD) algorithms for codedivision multiple-access (CDMA) systems depends on the accuracy of channel estimates. Such estimates are typically ...
Abstract. We present a novel algorithm for approximating the parameters of a multivariate t-distribution. At the expense of a slightly decreased accuracy in the estimates, the prop...