Speaker
Prof. Dr. Andreas Vlachos
University of Sheffield
When: Mo, 09.07.18, 17:00
Where: Room B-201
Topic
Imitation learning, zero-shot learning and automated fact checking
Language: English
Abstract
In this talk I will give an overview of my research in machine learning for natural language processing. I will begin by introducing my work on imitation learning, a machine learning paradigm I have used to develop novel algorithms for structure prediction that have been applied successfully to a number of tasks such as semantic parsing, natural language generation and information extraction. Key advantages are the ability to handle large output search spaces and to learn with non-decomposable loss functions. Following this, I will discuss my work on zero-shot learning using neural networks, which enabled us to learn models that can predict labels for which no data was observed during training. I will conclude with my work on automated fact-checking, a challenge we proposed in order to stimulate progress in machine learning, natural language processing and, more broadly, artificial intelligence.
Bio
Dr. Andreas Vlachos is a lecturer at the University of Sheffield, working on the intersection of Natural Language Processing and Machine Learning. Current projects include natural language generation, automated fact-checking and imitation learning. He has also worked on semantic parsing, language modelling, information extraction, active learning, clustering and biomedical text mining. Previously he was a postdoc at the Machine Reading group at UCL working with Sebastian Riedel and the BBC R&D team. Before that I was a member of the NLIP group at the University of Cambridge working with Stephen Clark and a postdoc at the University of Wisconsin-Madison working with Mark Craven.
Contact
Prof. Dr. Chris Biemann
