The Chinese University of Hong Kong
Department of Computer Science and Engineering


Title: Inference from Outliers
Date: March 14, 2018 (Wednesday)
Time: 2:302:30. - 3:30 p.m.
Venue: Room 121, 1/F, Ho Sin-hang Engineering Building,
The Chinese University of Hong Kong,
Shatin, N.T.
Speaker: Professor Mahesan Niranjan
University of Southampton



Classic machine learning is largely about classification and regression problems. However, many practical problems of interest in genomics, condition monitoring, medical diagnostics and security are better posed as problems of detecting novelty. In this talk, I will describe two applications of extracting useful information from novel data, in problems relating to modelling cellular protein concentrations and the solubility of synthetic chemical molecules. The algorithmic framework poses a robust support vector regression problem and the resulting non-convex optimisation problem is solved using a difference-of-convex formalism. (Part of this work is supported by grant EP/N014189/1, "Joining the Dots: From Data to Insight" from the EPSRC).



Mahesan Niranjan is Professor of Electronics and Computer Science at the University of Southampton, UK. Prior to this appointment in 2008, he has held faculty positions at the Universities of Cambridge (1990-1998) and Sheffield (1999-2007). At the University of Sheffield, he has served as Head of Computer Science and as Dean of Engineering. His research interests are in the subject of Machine Learning, and he has worked on the algorithmic and applied aspects of the subject. Some of his work (e.g. the SARSA algorithm in Reinforcement Learning) have been fairly influential in the field. He has held several research grants from the Research Councils in the UK, and the European Union. Currently, his main focus is on architectures and algorithms for Deep Learning and inference problems that arise in computational biology. More information from:


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