A systematic comparison of various statistical alignment models
Computational Linguistics
Ultraconservative online algorithms for multiclass problems
The Journal of Machine Learning Research
An empirical study of smoothing techniques for language modeling
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
Support vector machine learning for interdependent and structured output spaces
ICML '04 Proceedings of the twenty-first international conference on Machine learning
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Statistical phrase-based translation
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Minimum error rate training in statistical machine translation
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Online large-margin training of dependency parsers
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
A discriminative global training algorithm for statistical MT
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the 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
ORANGE: a method for evaluating automatic evaluation metrics for machine translation
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Online Passive-Aggressive Algorithms
The Journal of Machine Learning Research
Minimum risk annealing for training log-linear models
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Online large-margin training of syntactic and structural translation features
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
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
Stabilizing minimum error rate training
StatMT '09 Proceedings of the Fourth Workshop on Statistical Machine Translation
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
Distributed training strategies for the structured perceptron
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
ACLDemos '10 Proceedings of the ACL 2010 System Demonstrations
Linguistic Structure Prediction
Linguistic Structure Prediction
KenLM: faster and smaller language model queries
WMT '11 Proceedings of the Sixth Workshop on Statistical Machine Translation
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Hope and fear for discriminative training of statistical translation models
The Journal of Machine Learning Research
Structured ramp loss minimization for machine translation
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Optimized online rank learning for machine translation
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Batch tuning strategies for statistical machine translation
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Topic models for dynamic translation model adaptation
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Short Papers - Volume 2
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The introduction of large-margin based discriminative methods for optimizing statistical machine translation systems in recent years has allowed exploration into many new types of features for the translation process. By removing the limitation on the number of parameters which can be optimized, these methods have allowed integrating millions of sparse features. However, these methods have not yet met with wide-spread adoption. This may be partly due to the perceived complexity of implementation, and partly due to the lack of standard methodology for applying these methods to MT. This papers aims to shed light on large-margin learning for MT, explicitly presenting the simple passive-aggressive algorithm which underlies many previous approaches, with direct application to MT, and empirically comparing several widespread optimization strategies.