Text Classification from Labeled and Unlabeled Documents using EM
Machine Learning - Special issue on information retrieval
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Mixtures of deterministic-probabilistic networks and their AND/OR search space
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Integer linear programming inference for conditional random fields
ICML '05 Proceedings of the 22nd international conference on Machine learning
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
The Proposition Bank: An Annotated Corpus of Semantic Roles
Computational Linguistics
Information extraction from research papers using conditional random fields
Information Processing and Management: an International Journal
Unsupervised learning of field segmentation models for information extraction
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Aggregation via set partitioning for natural language generation
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Modeling Discriminative Global Inference
ICSC '07 Proceedings of the International Conference on Semantic Computing
The importance of syntactic parsing and inference in semantic role labeling
Computational Linguistics
The necessity of syntactic parsing for semantic role labeling
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Learning and inference over constrained output
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Beyond the pipeline: discrete optimization in NLP
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
Generalized inference with multiple semantic role labeling systems
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
Cross-task knowledge-constrained self training
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Unsupervised constraint driven learning for transliteration discovery
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
From information to knowledge: harvesting entities and relationships from web sources
Proceedings of the twenty-ninth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Inference with constrained hidden markov models in prism
Theory and Practice of Logic Programming
Minimally-supervised extraction of entities from text advertisements
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Find your advisor: robust knowledge gathering from the web
Procceedings of the 13th International Workshop on the Web and Databases
Posterior Regularization for Structured Latent Variable Models
The Journal of Machine Learning Research
Exploiting background knowledge for relation extraction
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Modeling relations and their mentions without labeled text
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part III
Scalable knowledge harvesting with high precision and high recall
Proceedings of the fourth ACM international conference on Web search and data mining
SCAD: collective discovery of attribute values
Proceedings of the 20th international conference on World wide web
Rich prior knowledge in learning for NLP
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Tutorial Abstracts of ACL 2011
Itemset mining: A constraint programming perspective
Artificial Intelligence
Database foundations for scalable RDF processing
RW'11 Proceedings of the 7th international conference on Reasoning web: semantic technologies for the web of data
Coupled temporal scoping of relational facts
Proceedings of the fifth ACM international conference on Web search and data mining
Minimally supervised event causality identification
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Exploiting partial annotations with EM training
WILS '12 Proceedings of the NAACL-HLT Workshop on the Induction of Linguistic Structure
Hierarchical conversation structure prediction in multi-party chat
SIGDIAL '12 Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue
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Probabilistic modeling has been a dominant approach in Machine Learning research. As the field evolves, thc problems of interest become increasingly challenging and complex. Making complex decisions in real world problems often involves assigning values to sets of interdependent variables where the expressive dependency structure can influence, or even dictate, what assignments are possible. However, incorporating nonlocal depcndencies in a probabilistic model can lead to intractable training and inference. This paper presents Constraints Conditional Models (CCMs), a framework that augments probabilistic models with declarative constraints as a way to support decisions in an expressive output space while maintaining modularity and tractability of training. We further show that declarative constraints can be used to take advantage of unlabeled data when training the probabilistic model.