Dr. Sean B. Holden

Sean B. Holden, Ph.D. is Senior Lecturer in Computer Science at the University of Cambridge Computer Laboratory and Cambridge Project for Existential Risk advisor.
 
Sean’s research covers assorted issues in both theoretical and applied machine learning. At present he is interested in:

• Computational learning theory. How can we better understand the properties of machine learning algorithms in terms of, for example, the relationship between the number of training examples used and their performance?
• Bayesian inference. This approach to machine learning continues to offer state-of-the-art performance in many applications. However the continuing problem of the analytical intractability of many of the fundamental calculations continues to provide opportunities for research into improved approximation techniques.
• Quantum computation for machine learning. It is known that, should a practical quantum computer become viable, quantum computation will provide definite benefits in certain areas. However little is known about the extent to which it might benefit machine learning.
• Machine learning techniques for automated theorem proving.

Sean’s papers include The Generalized FITC Approximation, 3D Analysis of Facial Morphology, Cross-Validation for Binary Classification by Real-Valued Functions: Theoretical Analysis, Quantifying Generalization in Linearly Weighted Neural Networks, Modeling the Model Athlete: Automatic Coaching of Rowing Technique, Handling Goal Utility Dependencies in a Satisfiability Framework, Robust Regression with Twinned Gaussian Processes, and PAC-like upper bounds for the sample complexity of leave-one-out cross-validation. Read the full list of his publications!
 
Sean earned his BSc in Electronic Systems Engineering from the University of East Anglia in 1989 and his Ph.D. in Engineering at Corpus Christi College in 1994. He did postdoctoral work in the Signals, Circuits, and Systems Research Group at King’s College London, before moving back to Cambridge to do further postdoctoral research in the Speech, Vision, and Robotics Group,
 
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