Language and Computation Day 2013


Here is a provisional programme to be finalised nearer the day:

  • 09:45 Welcome; Recent activities of the LAC group
  • 10:00 Fawaz Alarfaj Enhancing Entity-Finding Using Adaptive-Windows
  • 10:20 Azhar Alhindi Profile-Based Document Summarisation
  • 10:40 Naoto Nishio Predicting the Quality of a Translation from the Attibutes of a Translator using ML
  • 11:00 [Coffee]
  • 11:10 Maha Althobaiti A Semi-supervised Learning Approach to Arabic NER.
  • 11:30 Ans Alghamdi Active Learning for Archaeological Named Entities
  • 11:50 Roseline Antai TBC
  • 12:10 Deirdre Lungley Sentiment Analysis of Patient Feedback
  • 12:30 [Lunch]
  • 14:00 Andreas Vlachos (University of Cambridge) INVITED TALK: Imitation learning for structured prediction in NLP
  • 15:00 Cliff O'Reilly Modelling Mental Spaces
  • 15:20 [Coffee]
  • 15:40 Florence Myles Using oral learner corpora for second language acquisition research
  • 16:00 Doug Arnold TBC
  • 16:20 Sonja Eisenbeiss, Naledi Kgolo, Sarah Schmid and Janina Fickel Experimental Linguistics in the Field: A Morphological Processing Study on Setswana Noun Derivations and a New Resource Repository
  • 16:40 [Tea]

  • We plan to have a quick drink on campus afterwards and more drinks later in Wivenhoe.


Welcome and Recent Activities of the LAC group
This talk will give an introduction to the group and an overview of what the group has been up to since the last LAC day.
Andreas Vlachos - Imitation learning for structured prediction in NLP
Imitation learning is a learning paradigm originally developed to learn robotic controllers from demonstrations by humans, e.g. autonomous helicopters from pilot's demonstrations. Recently, algorithms for structured prediction in NLP were proposed under this paradigm and have been applied successfully to a number of tasks such as information extraction and summarization. In this talk I will describe in detail two imitation learning algorithms, SEARN (Daume III et al., 2009) and DAGGER (Ross et al., 2011) and describe their application to biomedical event extraction and knowledge base population.


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