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Making Sense of Data - A Research Agenda

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If you have a question about this talk, please contact Zoubin Ghahramani.

The talk will comprise two parts. In the first (non-technical) part I will outline my long term research agenda which can be summed up as “making machine learning into an engineering discipline”. I will explain why i think it is not at present, and what needs to be done in order to make it so. A crucial part of this is to be able to describe machine learning problems in a declarative way (as opposed to merely describing candidate solutions).

In the second (technical) part, I will present an example of the sort of theory that I believe will help by showing how seemingly different problems are actually different perspectives of the same problem. Specifically I will discuss connections between the problem of estimating similarity of two distributions and binary classification problems.

This talk is part of the Machine Learning @ CUED series.

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