The mathematics of statistical machine translation: parameter estimation
Computational Linguistics - Special issue on using large corpora: II
Support vector machine learning for interdependent and structured output spaces
ICML '04 Proceedings of the twenty-first international conference on Machine learning
A second-order Hidden Markov Model for part-of-speech tagging
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Ranking algorithms for named-entity extraction: boosting and the voted perceptron
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
An SVM based voting algorithm with application to parse reranking
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Discriminative Reranking for Natural Language Parsing
Computational Linguistics
Online large-margin training of dependency parsers
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Coarse-to-fine n-best parsing and MaxEnt discriminative reranking
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
An end-to-end discriminative approach to machine translation
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Predicting Structured Data (Neural Information Processing)
Predicting Structured Data (Neural Information Processing)
Dependency Parsing
CoNLL-X shared task on multilingual dependency parsing
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Rich bitext projection features for parse reranking
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Kernel regression based machine translation
NAACL-Short '07 Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers
11,001 new features for statistical machine translation
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Learning to rank with (a lot of) word features
Information Retrieval
Reranking the Berkeley and brown parsers
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Improving bilingual projections via sparse covariance matrices
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
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The accuracy of many natural language processing tasks can be improved by a reranking step, which involves selecting a single output from a list of candidate outputs generated by a baseline system. We propose a novel family of reranking algorithms based on learning separate low-dimensional embeddings of the task's input and output spaces. This embedding is learned in such a way that prediction becomes a low-dimensional nearest-neighbor search, which can be done computationally efficiently. A key quality of our approach is that feature engineering can be done separately on the input and output spaces; the relationship between inputs and outputs is learned automatically. Experiments on part-of-speech tagging task in four languages show significant improvements over a baseline decoder and existing reranking approaches.