The concepts and methods of mathematical programming underlie many machine learning algorithms and yet remain relatively unknown outside the operational research community. After a brief overview of optimisation theory, we will introduce the standard-form linear and quadratic programmes. We will then formulate the well-known linear regression problem (and the lesser-known robust regression problem) as mathematical programmes, and present algorithms to solve them. Whilst the techniques we will cover are completely general, we will conclude with some applications from financial planning and portfolio management. No previous knowledge of mathematical programming is required, but please note that this talk contains formulae (and Python code).
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