WeSSLLI 2020
Deep Learning and the Nature
of Linguistic Representation
July 13-17, 2020
Shalom Lappin
University of Gothenburg, Queen Mary University of
London, and
King’s College London
The application of deep learning methods to
problems in natural language processing has generated significant progress
across a wide range of natural language processing tasks.
For some of these applications deep
learning models now approach or surpass human performance.
While the success of this approach has
transformed the engineering methods of machine learning in artificial
intelligence, the significance of these achievements for the modelling of human
learning and representation remains unclear.
This course will look at the application of
a variety of deep learning systems to several cognitively interesting NLP
tasks.
We will consider the extent to which this
work illuminates our understanding of the way in which humans acquire and
represent linguistic knowledge.
Course
Outline and Class Slides