A maximum entropy approach to natural language processing
Computational Linguistics
Algorithms on strings, trees, and sequences: computer science and computational biology
Algorithms on strings, trees, and sequences: computer science and computational biology
Making large-scale support vector machine learning practical
Advances in kernel methods
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
A new approximate maximal margin classification algorithm
The Journal of Machine Learning Research
TnT: a statistical part-of-speech tagger
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
Support vector machine learning for interdependent and structured output spaces
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Hierarchical document categorization with support vector machines
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Feature-rich part-of-speech tagging with a cyclic dependency network
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
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Estimating the Support of a High-Dimensional Distribution
Neural Computation
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Word-sense disambiguation for machine translation
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Structured Prediction, Dual Extragradient and Bregman Projections
The Journal of Machine Learning Research
Pegasos: Primal Estimated sub-GrAdient SOlver for SVM
Proceedings of the 24th international conference on Machine learning
(Meta-) evaluation of machine translation
StatMT '07 Proceedings of the Second Workshop on Statistical Machine Translation
Context-aware discriminative phrase selection for statistical machine translation
StatMT '07 Proceedings of the Second Workshop on Statistical Machine Translation
IEEE Transactions on Signal Processing
Exploiting long-range dependencies in protein β-sheet secondary structure prediction
PRIB'10 Proceedings of the 5th IAPR international conference on Pattern recognition in bioinformatics
Exploitation of Machine Learning Techniques in Modelling Phrase Movements for Machine Translation
The Journal of Machine Learning Research
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We propose a structured learning approach, max-margin structure (MMS), which is targeted at natural language processing (NLP) tasks. The architecture of our approach is shown to capture structural aspects of the problem domains, leading to demonstrable performance improvements on two NLP tasks: part-of-speech tagging and statistical machine translation (SMT). We present a perceptron-based online learning algorithm to train the model and demonstrate desirable computational scaling behavior over traditional optimisation methods.