Sc. B. Brown University 1999, Ph. D. Johns Hopkins 2006, UMass Amherst post-doc 2005-2007. Research Interests: Natural Language Processing (in particular Information Extraction) and Machine Learning (in particular Semi-supervised learning).
Efficient Large-Scale Distributed Training of Conditional Maximum Entropy Models, Gideon Mann, Ryan McDonald, Mehryar Mohri, Nathan Silberman, Daniel Walker IV, Neural Information Processing Systems (NIPS), 2009.
Semi-supervised Learning of Dependency Parsers using Generalized Expectation Criteria, Gregory Druck, Gideon S. Mann, Andrew McCallum, IJCNLP-ACL, 2009.
Generalized Expectation Criteria for Semi-Supervised Learning of Conditional Random Fields, Gideon Mann, Andrew McCallum, ACL, 2008.
Learning From Labeled Features Using Generalized Expectation Criteria, Gregory Druck, Gideon Mann, Andrew McCallum, Proc. 31st International ACM SIGIR Conference on Research and Development in Information Retrieval, 2008, pp. 595-602.
Leveraging Existing Resources using Generalized Expectation Criteria, Gregory Druck, Gideon Mann, Andrew McCallum, NIPS Workshop on Learning Problem Design, 2007.