Structured Prediction with Deep Learning

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Structured prediction is concerned with predicting multiple interdependent variables. This project will develop the fundamental science for the next generation of structured-prediction algorithms, which will have a significant impact on a large variety of applications, such as social graphs, natural language processing, action recognition and computational biology. We develop techniques for deep learning of features in structured prediction, along with Bayesian approaches for the characterisation and quantification of uncertainty. The immediate impact of these will be reflected in better accuracy of the resulting algorithms and in a significant reduction in the amount of annotated data they require for learning.

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Supervisory team

Computer Science and Engineering

Business School

Computer Science and Engineering

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