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COLT
1998
Springer
13 years 9 months ago
Learning One-Variable Pattern Languages in Linear Average Time
A new algorithm for learning one-variable pattern languages is proposed and analyzed with respect to its average-case behavior. We consider the total learning time that takes into...
Rüdiger Reischuk, Thomas Zeugmann
ALT
1997
Springer
13 years 8 months ago
Learning One-Variable Pattern Languages Very Efficiently on Average, in Parallel, and by Asking Queries
A pattern is a string of constant and variable symbols. The language generated by a pattern is the set of all strings of constant symbols which can be obtained from by substituti...
Thomas Erlebach, Peter Rossmanith, Hans Stadtherr,...
ICGI
1998
Springer
13 years 9 months ago
Learning k-Variable Pattern Languages Efficiently Stochastically Finite on Average from Positive Data
Abstract. The present paper presents a new approach of how to convert Gold-style [4] learning in the limit into stochastically finite learning with high confidence. We illustrate t...
Peter Rossmanith, Thomas Zeugmann
ICDE
2008
IEEE
203views Database» more  ICDE 2008»
14 years 6 months ago
Training Linear Discriminant Analysis in Linear Time
Linear Discriminant Analysis (LDA) has been a popular method for extracting features which preserve class separability. It has been widely used in many fields of information proces...
Deng Cai, Xiaofei He, Jiawei Han
EACL
2006
ACL Anthology
13 years 6 months ago
Making Tree Kernels Practical for Natural Language Learning
In recent years tree kernels have been proposed for the automatic learning of natural language applications. Unfortunately, they show (a) an inherent super linear complexity and (...
Alessandro Moschitti