Inducing Features of Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
Selecting weighting factors in logarithmic opinion pools
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Shallow parsing with conditional random fields
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Introduction to the CoNLL-2000 shared task: chunking
ConLL '00 Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7
A comparison of algorithms for maximum entropy parameter estimation
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
Active learning for HPSG parse selection
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Introduction to the CoNLL-2003 shared task: language-independent named entity recognition
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Language independent NER using a maximum entropy tagger
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Scaling conditional random fields using error-correcting codes
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Efficiently inducing features of conditional random fields
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Scaling conditional random fields using error-correcting codes
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Context-based morphological disambiguation with random fields
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Reducing weight undertraining in structured discriminative learning
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Minimum risk annealing for training log-linear models
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Active learning and logarithmic opinion pools for hpsg parse selection
Natural Language Engineering
Partitioned logistic regression for spam filtering
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Using gazetteers in discriminative information extraction
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
CCG supertags in factored statistical machine translation
StatMT '07 Proceedings of the Second Workshop on Statistical Machine Translation
Graphical models over multiple strings
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Products of random latent variable grammars
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Context-free reordering, finite-state translation
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Posterior Regularization for Structured Latent Variable Models
The Journal of Machine Learning Research
Self-training with products of latent variable grammars
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Latent mixture of discriminative experts for multimodal prediction modeling
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Products of weighted logic programs
Theory and Practice of Logic Programming
Modeling wisdom of crowds using latent mixture of discriminative experts
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
Computational study of human communication dynamic
J-HGBU '11 Proceedings of the 2011 joint ACM workshop on Human gesture and behavior understanding
Regularisation techniques for conditional random fields: parameterised versus parameter-free
IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing
Simple semi-supervised learning for prepositional phrase attachment
IWPT '11 Proceedings of the 12th International Conference on Parsing Technologies
Mixing multiple translation models in statistical machine translation
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
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Recent work on Conditional Random Fields (CRFs) has demonstrated the need for regularisation to counter the tendency of these models to overfit. The standard approach to regularising CRFs involves a prior distribution over the model parameters, typically requiring search over a hyperparameter space. In this paper we address the overfitting problem from a different perspective, by factoring the CRF distribution into a weighted product of individual "expert" CRF distributions. We call this model a logarithmic opinion pool (LOP) of CRFs (LOP-CRFs). We apply the LOP-CRF to two sequencing tasks. Our results show that unregularised expert CRFs with an unregularised CRF under a LOP can outperform the unregularised CRF, and attain a performance level close to the regularised CRF. LOP-CRFs therefore provide a viable alternative to CRF regularisation without the need for hyperparameter search.