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» Global Learning of Labeled Dependency Trees
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EMNLP
2007
13 years 6 months ago
Online Learning for Deterministic Dependency Parsing
Deterministic parsing has emerged as an effective alternative for complex parsing algorithms which search the entire search space to get the best probable parse tree. In this pape...
Prashanth Mannem
PODS
2010
ACM
170views Database» more  PODS 2010»
13 years 10 months ago
A learning algorithm for top-down XML transformations
A generalization from string to trees and from languages to translations is given of the classical result that any regular language can be learned from examples: it is shown that ...
Aurélien Lemay, Sebastian Maneth, Joachim N...
ICML
2010
IEEE
13 years 5 months ago
Random Spanning Trees and the Prediction of Weighted Graphs
We show that the mistake bound for predicting the nodes of an arbitrary weighted graph is characterized (up to logarithmic factors) by the cutsize of a random spanning tree of the...
Nicolò Cesa-Bianchi, Claudio Gentile, Fabio...
ECML
2007
Springer
13 years 11 months ago
Probabilistic Models for Action-Based Chinese Dependency Parsing
Action-based dependency parsing, also known as deterministic dependency parsing, has often been regarded as a time efficient parsing algorithm while its parsing accuracy is a littl...
Xiangyu Duan, Jun Zhao, Bo Xu
ICDM
2010
IEEE
127views Data Mining» more  ICDM 2010»
13 years 2 months ago
Learning Markov Network Structure with Decision Trees
Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...
Daniel Lowd, Jesse Davis