Université de Genève
Tel: +41 22 379 00 60
Chargé de Cours, Department of Computer Science, University of Geneva
Most of the time:
Principal Scientist of the Parsing and Semantics group at Xerox Research Centre Europe, in Grenoble.
Maître d'Enseignement et de Recherche (MER) (something like Associate Professor, or Research Professor), Department of Computer Science, University of Geneva
James Henderson is a Chargé de Cours in the Department of Computer Science of the University of Geneva, which is part of the Centre Universitaire d'Informatique. He is co-head of the interdisciplinary research group Computational Learning and Computational Linguistics. He is now finishing his term as a member of the Editorial Board for the journal Computational Linguistics.
Previously, Dr Henderson was a Maître d'Enseignement et de Recherche (MER) in the Department of Computer Science of the University of Geneva. Before returning to Geneva, he was a Research Fellow in the Institute for Communicating and Collaborative Systems at the University of Edinburgh . Prior to that he held the position of Maître-Assistant in the AI Lab in the Department of Computer Science at the University of Geneva. And before that he held the position of Lecturer in the then Department of Computer Science at the University of Exeter, UK.
Dr Henderson received his PhD and MSc from the University of Pennsylvania, and his BSc from the Massachusetts Institute of Technology, USA.
- PARLANCE Project: Statistical spoken dialogue systems, open-domain information extraction, spoken language understanding
- Inducing Semantic Representations from Multiple Data Sources
- COMTIS: Improving the Coherence of Machine Translation Output by Modeling Intersentential Relations
- Sampling and Regularization for Latent Structure Models with Feature Induction
- Latent Variable Models for Structure Processing applied to Broad Coverage Natural Language Parsing
- CLASSiC Project: Spoken language understanding; End-to-end statistical dialogue systems
- Neural Networks for Structure Processing applied to Broad Coverage Natural Language Parsing
- TALK Project: Reinforcement Learning for dialog management
TRBM Dependency Parser:
The statistical dependency parser described in [Garg and Henderson, ACL 2011 (short papers)].
SSN Statistical Parser: A broad coverage natural language syntactic parser.
ISBN Dependency Parser: The statistical dependency parser described in [Titov and Henderson, IWPT 2007] and evaluated in [Titov and Henderson, EMNLP-CoNLL 2007].
Also see Andrea Gesmundo's web page.
Ivan Titov, Saarland University
Lonneke van der Plas, University of Stuttgart
Paola Merlo, University of Geneva
Joel Lang, University of Geneva
Oliver Lemon, Heriot-Watt University
Kallirroi Georgila, USC Institute for Creative Technologies
Gabriele Musillo, dMetrics
Andrea Gesmundo, University of Geneva
Nikhil Garg, University of Geneva
G.Gesmundo, J.Henderson, Undirected Machine Translation with Discriminative Reinforcement Learning. EACL 2014, Gothenburg, Sweden, 2014.
J.Henderson, P.Merlo, I.Titov, and G.Musillo, Multilingual Joint Parsing of Syntactic and Semantic Dependencies with a Latent Variable Model. Computational Linguistics, December 2013, Vol. 39, No. 4.
J.Lang and J.Henderson, Graph-Based Seed Set Expansion For Relation Extraction Using Random Walk Hitting Times. NAACL 2013, Atlanta, Georgia, USA, 2013.
Helen Hastie, Marie-Aude Aufaure, Panos Alexopoulos, Heriberto Cuayáhuitl, Nina Dethlefs, Milica Gasic, James Henderson, Oliver Lemon, Xingkun Liu, Peter Mika, Nesrine Ben Mustapha, Verena Rieser, Blaise Thomson, Pirros Tsiakoulis, Yves Vanrompay, Boris Villazon-Terrazas, Steve Young, Demonstration of the Parlance system: a data-driven, incremental, spoken dialogue system for interactive search. SIGDIAL 2013.
N.Garg and J.Henderson, Unsupervised Semantic Role Induction with Global Role Ordering. ACL 2012, Jeju Island, Korea, 2012.
A.Gesmundo, G.Satta, and J.Henderson, Heuristic Cube Pruning in Linear Time. ACL 2012, Jeju Island, Korea, 2012.
J.Henderson. Bayesian Network Automata for Modelling Unbounded Structures. IWPT, Dublin, Ireland, 2011.
A.Gesmundo and J.Henderson. Heuristic Search for Non-Bottom-Up Tree Structure Prediction. EMNLP, Edinburgh, UK, 2011.
N.Garg and J.Henderson. Temporal Restricted Boltzmann Machines for Dependency Parsing. ACL, Portland, Oregon, 2011.
L.van der Plas, P.Merlo, and J.Henderson. Scaling up Cross-Lingual Semantic Annotation Transfer. ACL, Portland, Oregon, 2011.
J.Henderson and I.Titov. Incremental Sigmoid Belief Networks for Grammar Learning. Journal of Machine Learning Research, 11(Dec):3541-3570, 2010.
A.Gesmundo and J.Henderson. Faster Cube Pruning. International Workshop on Spoken Language Translation (IWSLT), Paris, France, 2010.
J.Henderson. Artificial Neural Networks. A.Clark, C.Fox, and S.Lappin, editors, Handbook of Computational Linguistics and Natural Language Processing (Blackwell), 2010.
I.Titov and J.Henderson. A Latent Variable Model for Generative Dependency Parsing. In H. Bunt, P. Merlo and J. Nivre, editors, Trends in Parsing Technology. Text, Speech and Language Technology Series (Springer) 2010.
A.Gesmundo, J.Henderson, P.Merlo, and I.Titov. A Latent Variable Model of Synchronous Syntactic-Semantic Parsing for Multiple Languages. CoNLL 2009 Shared Task, Conf. on Computational Natural Language Learning (CoNLL-09), Boulder, CO, 2009.
L.van der Plas, J.Henderson, and P.Merlo. Domain Adaptation with Artificial Data for Semantic Parsing of Speech. NAACL, Boulder, CO, 2009.
I.Titov, J.Henderson, P.Merlo, and G.Musillo. Online Graph Planarisation for Synchronous Parsing of Semantic and Syntactic Dependencies. IJCAI-09, Pasadena, California, USA, 2009.
K.Georgila, O.Lemon, J.Henderson, and J.D.Moore. Automatic annotation of context and speech acts for dialogue corpora. Natural Language Engineering, 15(03):315-353, 2009.
J.Henderson, O.Lemon, K.Georgila. Hybrid reinforcement/supervised learning of dialogue policies from fixed data sets. Computational Linguistics, 34(4):487-511, 2008.
J.Henderson, P.Merlo, G.Musillo, I.Titov A Latent Variable Model of Synchronous Parsing for Syntactic and Semantic Dependencies. CoNLL 2008 Shared Task, Conf. on Computational Natural Language Learning (CoNLL-08), Manchester, UK, 2008.
J.Henderson and O.Lemon. Mixture model POMDPs for efficient handling of uncertainty in dialogue management. In Proc. 46th Annual Meeting of the Association for Computational Linguistics (ACL'08), Columbus, Ohio, 2008.
I.Titov and J.Henderson. Incremental Bayesian Networks for Structure Prediction. In Proc. 24th International Conference on Machine Learning (ICML 2007), Corvallis, OR, USA , 2007.
I.Titov and J.Henderson. Constituent Parsing with Incremental Sigmoid Belief Networks. In Proc. 45th Meeting of Association for Computational Linguistics (ACL 2007), Prague, Czech Republic, 2007.
I.Titov and J.Henderson. A Latent Variable Model for Generative Dependency Parsing. In Proc. International Conference on Parsing Technologies (IWPT 2007), Prague, Czech Republic, 2007.
I.Titov and J.Henderson. Fast and Robust Multilingual Dependency Parsing with a Generative Latent Variable Model. In Proc. Joint Conf. on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL 2007), Prague, Czech Republic, 2007. (CoNLL Shared Task, 3rd result out of 23)
I.Titov and J.Henderson. Loss minimization in parse reranking. In Proc. 2006 Conf. on Empirical Methods in Natural Language Processing (EMNLP 2006), Sydney, Australia, 2006.
I.Titov and J.Henderson. Porting statistical parsers with data-defined kernels. In Proc. Tenth Conf. on Computational Natural Language Learning (CoNLL 2006), New York, NY, USA, 2006.
I.Titov and J.Henderson. Bayes Risk Minimization in Natural Language Parsing. Technical report. University of Geneva, 2006. [Send email to Ivan Titov if you would like the implementation]
J.Henderson and I.Titov. Data-defined kernels for parse reranking derived from probabilistic models. In Proc. 43nd Meeting of Association for Computational Linguistics (ACL 2005), Ann Arbor, MI, USA, 2005.
I.Titov and J.Henderson. Deriving kernels from MLP probability estimators for large categorization problems. In Proc. 2005 International Joint Conf. on Neural Networks (IJCNN 2005), Montreal, Quebec, Canada, 2005.
J.Henderson, O.Lemon, and K.Georgila. Hybrid reinforcement/supervised learning for dialogue policies from COMMUNICATOR data. In Proc. IJCAI workshop on Knowledge and Reasoning in Practical Dialogue Systems, Edinburgh, UK, 2005.
K.Georgila, J.Henderson, and O.Lemon. Learning User Simulations for Information State Update Dialogue Systems. In Proc. 9th European Conf. on Speech Communication and Technology (INTERSPEECH - EUROSPEECH 2005), Lisbon, Portugal, 2005.
K.Georgila, O.Lemon, and J.Henderson. Automatic annotation of COMMUNICATOR dialogue data for learning dialogue strategies and user simulations. In Proc. Ninth Workshop on the Semantics and Pragmatics of Dialogue (SEMDIAL: DIALOR 2005), Nancy, France, 2005.
J.Henderson. Discriminative training of a neural network statistical parser. In Proc. 42nd Meeting of Association for Computational Linguistics (ACL 2004), Barcelona, Spain, 2004.
J.Henderson. Lookahead in deterministic left-corner parsing. In Proc. Workshop on Incremental Parsing: Bringing Engineering and Cognition Together, Barcelona, Spain, 2004.
J.Henderson. Estimating Probabilities for Unbounded Categorization Problems. Neurocomputing, 57:77--86, 2004.
J.Henderson. A neural network parser that handles sparse data. In H. Bunt, J. Carroll, and G. Satta, editors, New Developments in Parsing Technology. Kluwer, Boston/Dordrecht/London, 2004.
J.Henderson. Inducing History Representations for Broad Coverage Statistical Parsing. In Proceedings of the joint meeting of the North American Chapter of the Association for Computational Linguistics and the Human Language Technology Conference (HLT-NAACL 2003), pages 103-110, Edmonton, Canada, 2003.
J.Henderson. Structural Bias in Inducing Representations for Probabilistic Natural Language Parsing. In Proceedings of 13th Int. Conf. on Artificial Neural Networks (ICANN/ICONIP 2003), Istanbul, Turkey, 2003.
J.Henderson. Generative Versus Discriminative Models for Statistical Left-Corner Parsing. In Proceedings of 8th Int Workshop on Parsing Technologies (IWPT 2003), pages 115-126, Nancy, France, 2003.
J.Henderson. Neural network probability estimation for broad coverage parsing. In Proceedings of 10th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2003), pages 131-138, Budapest, Hungary, 2003.
P.Lane and J.Henderson. Towards effective parsing with neural networks: Inherent generalization and bounded resource effects. Applied Intelligence, 19(1):83-99, 2003.
J.Henderson, P.Merlo, I.Petroff, and G.Schneider. Using Syntactic Analysis to Increase Efficiency in Visualizing Text Collections. In Proceedings of the 19th International Conference on Computational Linguistics (COLING 2002), pages 335-341, Taipei, Taiwan, 2002.
J.Henderson, P.Merlo, I.Petroff, and G.Schneider. Using NLP to Efficiently Visualize Text Collections with SOMs. In Proceedings of the 3rd International Workshop on Natural Language and Information Systems (NLIS 2002), Aix-en-Provence, France, 2002.
J.Henderson. Estimating Probabilities for Unbounded Categorization Problems. In Proceedings the 10th European Symposium on Artificial Neural Networks (ESANN 2002), pages 383-388, Bruges, Belgium, 2002.
P.Lane and J.Henderson. Incremental Syntactic Parsing of Natural Language Corpora with Simple Synchrony Networks. In IEEE Transactions on Knowledge and Data Engineering, 13(2), 2001.
J.Henderson. Segmenting State into Entities and its Implication for Learning. In S.Wermter, J.Austin, and D.Willshaw, editors, Emergent Neural Computational Architectures based on Neuroscience, pages 227-236. Springer-Verlag, Heidelberg, Germany, 2001.
J.Henderson. Estimating a Probabilistic Grammar Using a Neural Network In Proceedings of the 1st workshop on Robust Methods in Analysis of Natural Language Data (ROMAND 2000), Lausanne, Switzerland, 2000.
J.Henderson. Segmenting State into Entities and its Implication for Learning In Proceedings of the International Workshop on Current Computational Architectures Integrating Neural Networks and Neuroscience (EmerNet 2000), Durham, UK, 2000.
J.Henderson. A Neural Network Parser that Handles Sparse Data. In Proceedings of the 6th International Workshop on Parsing Technologies (IWPT 2000), pages 123-134, Trento, Italy, 2000.
J.Henderson. Constituency, Context, and Connectionism in Syntactic Parsing. In M.Crocker, M.Pickering, and C.Clifton, editors, Architectures and Mechanisms for Language Processing, pages 189--209. Cambridge University Press, Cambridge UK, 2000.
J.Henderson and P.Lane. A Connectionist Architecture for Learning to Parse. In Proceedings of 17th International Conference on Computational Linguistics and the 36th Annual Meeting of the Association for Computational Linguistics (COLING-ACL`98), pages 531-537, University of Montreal, Canada, 1998.
P.Lane and J.Henderson. Simple Synchrony Networks: Learning to Parse Natural Language with Temporal Synchrony Variable Binding. In Proceedings of the 1998 International Conference on Artificial Neural Networks (ICANN`98), pages 615-620, Skövde, Sweden, 1998.
J.Henderson. A Connectionist Architecture with Inherent Systematicity. In Proceedings of the Cognitive Science Society (CogSci`96), pages 574--579, La Jolla, CA, 1996.
J.Henderson. Connectionist Syntactic Parsing Using Temporal Variable Binding. Journal of Psycholinguistic Research, 23(5):353--379, 1994.
J.Henderson. Description Based Parsing in a Connectionist Network. PhD thesis, University of Pennsylvania, Philadelphia, PA. Technical Report MS-CIS-94-46, 1994.
J.Henderson. A Connectionist Parser for Structure Unification Grammar. In Proceedings of the 30th Annual Meeting of the Association for Computational Linguistics (ACL`92), Newark, DE, 1992.
J.Henderson. A Structural Interpretation of Combinatory Categorial Grammar. Technical Report MS-CIS-92-49, University of Pennsylvania, Philadelphia, PA, 1992.
J.Henderson. Structure Unification Grammar: A Unifying Framework For Investigating Natural Language. Masters thesis, University of Pennsylvania, Philadelphia, PA. Technical Report MS-CIS-90-94, 1990.
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"Exact inference is futile; µ will be approximated."