Workshop on Learning with Structured Data and applications on Natural Language and Biology
9th to 11th December 2015
This workshop aims at presenting recent advances in Machine Learning field of Structured Prediction. The goal of structured prediction is to learn from data for which an underlying structure exists (e.g. a graph) as well as produce a graph as output. Both theoretical and practical issues will be addressed by the invited speakers. Topics include structured and incremental perceptrons, Maximum Entropy Markov Models, Conditional Random Fields, Maximum Margin Markov Networks, SVMs for Interdependent and Structured Outputs. particular attention will be given to applications in Natural Language Processing (in areas such as syntactic analysis and discourse analysis) and biology.
The last day of the workshop will be devoted to a special course "deep learning : background and application to natural language processing" given by Alexandre Allauzen (LIMSI, Université Paris-Sud XI).
Location
Participation to the workshop is free of charge but a pre-registration is required (click here for registration)
Booklet
List of abstracts is available here
PDF booklet that will be distributed at the workshop is available here
The schedule is available here
The prereqquisite and the subject for the Deep learning Hands-on computer session is available here
List of Invited Speakers
- André Martins, university of Priberam
- Alexandre Allauzen, university of Paris-Sud XI
- Andreas Vlachos, University of Sheffield
- Alessandro Moschitti, University of Trento and Qatar Computing Research Institute
- Xavier Carreras, Xerox
- Ariadna Quattoni, Xerox
- Pascal Denis, INRIA Lille
- Christophe Gonzales, LIP-6 Paris
- Hachem Kadri, university of marseille
- Christrine Sinoquet, Nantes
- James Cussens, university of York
- Francois Coste, Inria Rennes
- Jian-Yun Nie, university of Montréal
- Eustasio del Barrio, Universidad de Valladolid