Neural networks and the bias/variance dilemma
Neural Computation
An efficient implementation of a new DOP model
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 1
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
An all-subtrees approach to unsupervised parsing
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Reducing Bias Effects in DOP Parameter Estimation
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Darwinised data-oriented parsing: statistical NLP with added sex and death
CACLA '09 Proceedings of the EACL 2009 Workshop on Cognitive Aspects of Computational Language Acquisition
Unsupervised parsing with U-DOP
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Theoretical evaluation of estimation methods for data-oriented parsing
EACL '06 Proceedings of the Eleventh Conference of the European Chapter of the Association for Computational Linguistics: Posters & Demonstrations
Inducing compact but accurate tree-substitution grammars
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
A unified model of structural organization in language and music
Journal of Artificial Intelligence Research
A Bayesian model of syntax-directed tree to string grammar induction
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Accuracy-based scoring for DOT: towards direct error minimization for data-oriented translation
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Simple, accurate parsing with an all-fragments grammar
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Head-modifier relation based non-lexical reordering model for phrase-based translation
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Re-structuring, re-labeling, and re-aligning for syntax-based machine translation
Computational Linguistics
Inducing Tree-Substitution Grammars
The Journal of Machine Learning Research
Panning for EBMT gold, or "Remembering not to forget"
Machine Translation
Accurate parsing with compact tree-substitution grammars: Double-DOP
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
A new general grammar formalism for parsing
MICAI'11 Proceedings of the 10th Mexican international conference on Advances in Artificial Intelligence - Volume Part I
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A data-oriented parsing or DOP model for statistical parsing associates fragments of linguistic representations with numerical weights, where these weights are estimated by normalizing the empirical frequency of each fragment in a training corpus (see Bod [1998] and references cited therein). This note observes that this estimation method is biased and inconsistent; that is, the estimated distribution does not in general converge on the true distribution as the size of the training corpus increases.