Minimization methods for non-differentiable functions
Minimization methods for non-differentiable functions
Mathematical Programming: Series A and B
Machine Learning
Coarse-to-fine n-best parsing and MaxEnt discriminative reranking
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
A fast finite-state relaxation method for enforcing global constraints on sequence decoding
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Online Passive-Aggressive Algorithms
The Journal of Machine Learning Research
Hierarchical Phrase-Based Translation
Computational Linguistics
Efficient projections onto the l1-ball for learning in high dimensions
Proceedings of the 25th international conference on Machine learning
Graphical Models, Exponential Families, and Variational Inference
Graphical Models, Exponential Families, and Variational Inference
Polyhedral outer approximations with application to natural language parsing
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
CoNLL-X shared task on multilingual dependency parsing
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Multilingual dependency analysis with a two-stage discriminative parser
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Labeled pseudo-projective dependency parsing with support vector machines
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
TAG, dynamic programming, and the perceptron for efficient, feature-rich parsing
CoNLL '08 Proceedings of the Twelfth Conference on Computational Natural Language Learning
The CoNLL-2008 shared task on joint parsing of syntactic and semantic dependencies
CoNLL '08 Proceedings of the Twelfth Conference on Computational Natural Language Learning
Incremental integer linear programming for non-projective dependency parsing
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Summarization with a joint model for sentence extraction and compression
ILP '09 Proceedings of the Workshop on Integer Linear Programming for Natural Langauge Processing
Dependency-based semantic role labeling of PropBank
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
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
Sparse multi-scale grammars for discriminative latent variable parsing
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Global inference for sentence compression an integer linear programming approach
Journal of Artificial Intelligence Research
Concise integer linear programming formulations for dependency parsing
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
Efficient third-order dependency parsers
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Dynamic programming for linear-time incremental parsing
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
On dual decomposition and linear programming relaxations for natural language processing
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Turbo parsers: dependency parsing by approximate variational inference
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Dual decomposition for parsing with non-projective head automata
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Exact decoding of syntactic translation models through Lagrangian relaxation
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Jointly learning to extract and compress
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Learning dependency-based compositional semantics
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
An alternating direction method for dual MAP LP relaxation
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part II
An exact dual decomposition algorithm for shallow semantic parsing with constraints
SemEval '12 Proceedings of the First Joint Conference on Lexical and Computational Semantics - Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation
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
Parse, price and cut: delayed column and row generation for graph based parsers
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Linguistic structure prediction with the sparseptron
XRDS: Crossroads, The ACM Magazine for Students - Scientific Computing
Journal of Artificial Intelligence Research
Hi-index | 0.00 |
Dual decomposition has been recently proposed as a way of combining complementary models, with a boost in predictive power. However, in cases where lightweight decompositions are not readily available (e.g., due to the presence of rich features or logical constraints), the original subgradient algorithm is inefficient. We sidestep that difficulty by adopting an augmented Lagrangian method that accelerates model consensus by regularizing towards the averaged votes. We show how first-order logical constraints can be handled efficiently, even though the corresponding subproblems are no longer combinatorial, and report experiments in dependency parsing, with state-of-the-art results.