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ICGI
1998
Springer
13 years 8 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
ALT
2003
Springer
13 years 8 months ago
Can Learning in the Limit Be Done Efficiently?
Abstract. Inductive inference can be considered as one of the fundamental paradigms of algorithmic learning theory. We survey results recently obtained and show their impact to pot...
Thomas Zeugmann
SAGA
2001
Springer
13 years 9 months ago
Stochastic Finite Learning
Inductive inference can be considered as one of the fundamental paradigms of algorithmic learning theory. We survey results recently obtained and show their impact to potential ap...
Thomas Zeugmann