Class-based n-gram models of natural language
Computational Linguistics
A maximum entropy approach to natural language processing
Computational Linguistics
Combining labeled and unlabeled data with co-training
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
Learning to classify text from labeled and unlabeled documents
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Incorporating Prior Knowledge into Boosting
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
An Alternate Objective Function for Markovian Fields
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Transductive Inference for Text Classification using Support Vector Machines
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Learning from Labeled and Unlabeled Data using Graph Mincuts
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Tagging English text with a probabilistic model
Computational Linguistics
A corpus-based bootstrapping algorithm for Semi-Automated semantic lexicon construction
Natural Language Engineering
Unsupervised word sense disambiguation rivaling supervised methods
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
Kernel conditional random fields: representation and clique selection
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Incorporating Prior Knowledge into SVM for Image Retrieval
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Weakly supervised natural language learning without redundant views
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
ICML '05 Proceedings of the 22nd international conference on Machine learning
Understanding the Yarowsky Algorithm
Computational Linguistics
A comparison of algorithms for maximum entropy parameter estimation
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
Large scale semi-supervised linear SVMs
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data
The Journal of Machine Learning Research
Corpus-based induction of syntactic structure: models of dependency and constituency
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Contrastive estimation: training log-linear models on unlabeled data
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Unsupervised learning of field segmentation models for information extraction
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Word sense disambiguation using label propagation based semi-supervised learning
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Semi-supervised conditional random fields for improved sequence segmentation and labeling
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Prototype-driven grammar induction
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Prototype-driven learning for sequence models
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Simple, robust, scalable semi-supervised learning via expectation regularization
Proceedings of the 24th international conference on Machine learning
Semi-supervised classification with hybrid generative/discriminative methods
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Video suggestion and discovery for youtube: taking random walks through the view graph
Proceedings of the 17th international conference on World Wide Web
Estimating labels from label proportions
Proceedings of the 25th international conference on Machine learning
Learning from labeled features using generalized expectation criteria
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Learning from measurements in exponential families
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Semi-supervised sequence modeling with syntactic topic models
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
Semi-supervised learning of dependency parsers using generalized expectation criteria
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
Dependency grammar induction via bitext projection constraints
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
Active learning by labeling features
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Alternating projections for learning with expectation constraints
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
A new metric-based approach to model selection
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Transductive learning for text classification using explicit knowledge models
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
A framework for incorporating class priors into discriminative classification
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Domain adaptation for text categorization by feature labeling
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
Domain adaptation by constraining inter-domain variability of latent feature representation
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Semi-supervised SVMs for classification with unknown class proportions and a small labeled dataset
Proceedings of the 20th ACM international conference on Information and knowledge management
Training dependency parsers by jointly optimizing multiple objectives
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Learning structural dependencies of words in the Zipfian tail
IWPT '11 Proceedings of the 12th International Conference on Parsing Technologies
Unified expectation maximization
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Improved parsing and POS tagging using inter-sentence consistency constraints
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Constrained log-likelihood-based semi-supervised linear discriminant analysis
SSPR'12/SPR'12 Proceedings of the 2012 Joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
Semi-supervised linear discriminant analysis through moment-constraint parameter estimation
Pattern Recognition Letters
Joint semi-supervised learning of Hidden Conditional Random Fields and Hidden Markov Models
Pattern Recognition Letters
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In this paper, we present an overview of generalized expectation criteria (GE), a simple, robust, scalable method for semi-supervised training using weakly-labeled data. GE fits model parameters by favoring models that match certain expectation constraints, such as marginal label distributions, on the unlabeled data. This paper shows how to apply generalized expectation criteria to two classes of parametric models: maximum entropy models and conditional random fields. Experimental results demonstrate accuracy improvements over supervised training and a number of other state-of-the-art semi-supervised learning methods for these models.