While there is a lot of empirical evidence showing that traditional rule learning approaches work well in practice, it is nearly impossible to derive analytical results about thei...
Top Down Induction of Decision Trees (TDIDT) is the most commonly used method of constructing a model from a dataset in the form of classification rules to classify previously unse...
This paper describes a new approach to automatically learning linguistic knowledge for spelling correction. A major feature of this approach is the fact that the acquired knowledg...
This paper presents an unsupervised learning approach to building a non-English (Arabic) stemmer. The stemming model is based on statistical machine translation and it uses an Eng...
The ways in which an agent’s actions affect the world can often be modeled compactly using a set of relational probabilistic planning rules. This paper addresses the problem of ...
Ashwin Deshpande, Brian Milch, Luke S. Zettlemoyer...