Mathematics, Optimisation, and Statistics: Cutting-Edge Algorithms for Difficult Data

In this session, Ian details key enhancements in numerical modelling in MATLAB. The session highlights several optimisation problems and describes the plethora of algorithms, many new, available to solve them. Ian advises on architecting and programming optimisation models and how to use MATLAB to interpret and test solutions. He then outlines statistical developments relevant to high-dimensional and large data sets, examining regression, machine learning, and feature selection algorithms, such as discriminant analysis, loess regression, bagged decision trees, support vector machines, and neural networks. Ian also summarises new capabilities in symbolic math and curve fitting.