Gregory Druck
Gregory Druck
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Learning from labeled features using generalized expectation criteria
G Druck, G Mann, A McCallum
Proceedings of the 31st annual international ACM SIGIR conference on …, 2008
2992008
Active learning by labeling features
G Druck, B Settles, A McCallum
Proceedings of the 2009 conference on Empirical methods in natural language …, 2009
1792009
Multi-conditional learning: Generative/discriminative training for clustering and classification
A McCallum, C Pal, G Druck, X Wang
AAAI, 433-439, 2006
1312006
Semi-supervised classification with hybrid generative/discriminative methods
G Druck, C Pal, A McCallum, X Zhu
Proceedings of the 13th ACM SIGKDD international conference on Knowledge …, 2007
942007
Alternating projections for learning with expectation constraints
K Bellare, G Druck, A McCallum
arXiv preprint arXiv:1205.2660, 2012
772012
Learning to predict the quality of contributions to wikipedia
G Druck, G Miklau, A McCallum
WikiAI 8, 7-12, 2008
572008
Semi-supervised learning of dependency parsers using generalized expectation criteria
G Druck, G Mann, A McCallum
Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL …, 2009
532009
Generalized expectation criteria
A McCallum, G Mann, G Druck
Computer science technical note, University of Massachusetts, Amherst, MA 94 …, 2007
492007
High-performance semi-supervised learning using discriminatively constrained generative models
G Druck, A McCallum
Proceedings of the 27th International Conference on Machine Learning (ICML …, 2010
382010
Spice it up? Mining refinements to online instructions from user generated content
G Druck, B Pang
Proceedings of the 50th Annual Meeting of the Association for Computational …, 2012
232012
Toward interactive training and evaluation
G Druck, A McCallum
Proceedings of the 20th ACM international conference on Information and …, 2011
202011
Generalized expectation criteria for lightly supervised learning
G Druck
172011
Leveraging existing resources using generalized expectation criteria
G Druck, G Mann, A McCallum
Proceedings of NIPS Workshop on Learning Problem Design, 2007
92007
Reducing annotation effort using generalized expectation criteria
G Druck, G Mann, A McCallum
MASSACHUSETTS UNIV AMHERST DEPT OF COMPUTER SCIENCE, 2007
82007
Computing conditional feature covariance in non-projective tree conditional random fields
G Druck, D Smith
Technical Report UM-CS-2009-060, University of Massachusetts, 2009
32009
Rich prior knowledge in learning for natural language processing
G Druck, K Ganchev, J Graça
Proceedings of the 49th Annual Meeting of the Association for Computational …, 2011
22011
Learning A* priority function from unlabeled data
M Narasimhan, PA Viola, G Druck
US Patent 7,840,503, 2010
22010
Learning A* underestimates: Using inference to guide inference
G Druck, M Narasimhan, P Viola
Artificial Intelligence and Statistics, 99-106, 2007
22007
Rich prior knowledge in learning for NLP
G Druck, K Ganchev, J Graca
Proceedings of the 49th Annual Meeting of the Association for Computational …, 2011
12011
Constraint-Driven Training of Complex Models Using MCMC
S SINGH, G DRUCK, A MCCALLUM
2012
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Artikkelit 1–20