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RIA
2006
84views more  RIA 2006»
15 years 6 months ago
Learning Recursive Automata from Positive Examples
In this theoretical paper, we compare the "classical" learning techniques used to infer regular grammars from positive examples with the ones used to infer categorial gra...
Isabelle Tellier
ETAI
2000
84views more  ETAI 2000»
15 years 6 months ago
Learning Stochastic Logic Programs
Stochastic logic programs combine ideas from probabilistic grammars with the expressive power of definite clause logic; as such they can be considered as an extension of probabili...
Stephen Muggleton
ICIP
2010
IEEE
15 years 4 months ago
Learning simple texture discrimination filters
Current texture analysis methods enable good discrimination but are computationally too expensive for applications which require high frame rates. This occurs because they use red...
Rui F. C. Guerreiro, Pedro M. Q. Aguiar
ICPR
2010
IEEE
15 years 4 months ago
Semi-supervised Graph Learning: Near Strangers or Distant Relatives
In this paper, an easily implemented semi-supervised graph learning method is presented for dimensionality reduction and clustering, using the most of prior knowledge from limited...
Weifu Chen, Guocan Feng
ACL
2009
15 years 4 months ago
Semi-Supervised Active Learning for Sequence Labeling
While Active Learning (AL) has already been shown to markedly reduce the annotation efforts for many sequence labeling tasks compared to random selection, AL remains unconcerned a...
Katrin Tomanek, Udo Hahn