An Introduction to Variational Methods for Graphical Models
Machine Learning
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
A differential approach to inference in Bayesian networks
Journal of the ACM (JACM)
The harpy speech recognition system.
The harpy speech recognition system.
Parsing inside-out
Computational Linguistics
Inside-outside reestimation from partially bracketed corpora
ACL '92 Proceedings of the 30th annual meeting on Association for Computational Linguistics
Parameter estimation for probabilistic finite-state transducers
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Incorporating non-local information into information extraction systems by Gibbs sampling
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Compiling Comp Ling: practical weighted dynamic programming and the Dyna language
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Hidden-variable models for discriminative reranking
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Hierarchical Phrase-Based Translation
Computational Linguistics
Dependency parsing by belief propagation
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Probabilistic inference for machine translation
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Parsing '05 Proceedings of the Ninth International Workshop on Parsing Technology
Variational bayesian grammar induction for natural language
ICGI'06 Proceedings of the 8th international conference on Grammatical Inference: algorithms and applications
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Feature-rich translation by quasi-synchronous lattice parsing
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Statistical bistratal dependency parsing
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
Unsupervised word alignment with arbitrary features
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Generalized higher-order dependency parsing with cube pruning
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
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We introduce cube summing, a technique that permits dynamic programming algorithms for summing over structures (like the forward and inside algorithms) to be extended with non-local features that violate the classical structural independence assumptions. It is inspired by cube pruning (Chiang, 2007; Huang and Chiang, 2007) in its computation of non-local features dynamically using scored k-best lists, but also maintains additional residual quantities used in calculating approximate marginals. When restricted to local features, cube summing reduces to a novel semiring (k-best+residual) that generalizes many of the semirings of Goodman (1999). When non-local features are included, cube summing does not reduce to any semiring, but is compatible with generic techniques for solving dynamic programming equations.