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» A statistical approach to rule learning
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ICML
2004
IEEE
14 years 3 months ago
Towards tight bounds for rule learning
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...
Ulrich Rückert, Stefan Kramer
IFIP12
2008
13 years 11 months ago
P-Prism: A Computationally Efficient Approach to Scaling up Classification Rule Induction
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...
Frederic T. Stahl, Max A. Bramer, Mo Adda
ICML
1997
IEEE
14 years 10 months ago
Automatic Rule Acquisition for Spelling Correction
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...
Lidia Mangu, Eric Brill
ACL
2003
13 years 11 months ago
Unsupervised Learning of Arabic Stemming Using a Parallel Corpus
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...
Monica Rogati, J. Scott McCarley, Yiming Yang
DAGSTUHL
2007
13 years 11 months ago
Learning Probabilistic Relational Dynamics for Multiple Tasks
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...