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» Online Learning of Approximate Dependency Parsing Algorithms
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NECO
2008
112views more  NECO 2008»
13 years 7 months ago
Second-Order SMO Improves SVM Online and Active Learning
Iterative learning algorithms that approximate the solution of support vector machines (SVMs) have two potential advantages. First, they allow for online and active learning. Seco...
Tobias Glasmachers, Christian Igel
FUIN
2006
98views more  FUIN 2006»
13 years 7 months ago
On-line Approximate String Matching in Natural Language
We consider approximate pattern matching in natural language text. We use the words of the text as the alphabet, instead of the characters as in traditional string matching approac...
Kimmo Fredriksson
ECML
2007
Springer
14 years 1 months ago
Weighted Kernel Regression for Predicting Changing Dependencies
Abstract. Consider the online regression problem where the dependence of the outcome yt on the signal xt changes with time. Standard regression techniques, like Ridge Regression, d...
Steven Busuttil, Yuri Kalnishkan
NLP
2000
13 years 11 months ago
Monte-Carlo Sampling for NP-Hard Maximization Problems in the Framework of Weighted Parsing
Abstract. The purpose of this paper is (1) to provide a theoretical justification for the use of Monte-Carlo sampling for approximate resolution of NP-hard maximization problems in...
Jean-Cédric Chappelier, Martin Rajman
VLDB
2006
ACM
162views Database» more  VLDB 2006»
14 years 7 months ago
Dependency trees in sub-linear time and bounded memory
We focus on the problem of efficient learning of dependency trees. Once grown, they can be used as a special case of a Bayesian network, for PDF approximation, and for many other u...
Dan Pelleg, Andrew W. Moore