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» Online Learning of Approximate Dependency Parsing Algorithms
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COLING
2010
13 years 2 months ago
Kernel Slicing: Scalable Online Training with Conjunctive Features
This paper proposes an efficient online method that trains a classifier with many conjunctive features. We employ kernel computation called kernel slicing, which explicitly consid...
Naoki Yoshinaga, Masaru Kitsuregawa
WSOM
2009
Springer
14 years 2 months ago
Approaching the Time Dependent Cocktail Party Problem with Online Sparse Coding Neural Gas
Abstract. We show how the “Online Sparse Coding Neural Gas” algorithm can be applied to a more realistic model of the “Cocktail Party Problem”. We consider a setting where ...
Kai Labusch, Erhardt Barth, Thomas Martinetz
LREC
2010
159views Education» more  LREC 2010»
13 years 9 months ago
Improvements in Parsing the Index Thomisticus Treebank. Revision, Combination and a Feature Model for Medieval Latin
The creation of language resources for less-resourced languages like the historical ones benefits from the exploitation of language-independent tools and methods developed over th...
Marco Passarotti, Felice dell'Orletta
ML
1998
ACM
102views Machine Learning» more  ML 1998»
13 years 7 months ago
Statistical Mechanics of Online Learning of Drifting Concepts: A Variational Approach
We review the application of statistical mechanics methods to the study of online learning of a drifting concept in the limit of large systems. The model where a feed-forward netwo...
Renato Vicente, Osame Kinouchi, Nestor Caticha
IJCAI
2007
13 years 9 months ago
Simple Training of Dependency Parsers via Structured Boosting
Recently, significant progress has been made on learning structured predictors via coordinated training algorithms such as conditional random fields and maximum margin Markov ne...
Qin Iris Wang, Dekang Lin, Dale Schuurmans