This Sydney Workshop on Mathematics of Data Science aims to highlight leading-edge research in machine learning and data science, with a particular emphasis on addressing the mathematical, statistical, and computational challenges encountered in these fields,including machine learning, deep learning, and the most recent large AI models. Scheduled to take place at the School of Mathematics […]
Description: Many algorithms in mathematical optimisation work on the principle of breaking a complex problem into smaller, computationally tractable pieces and then exploiting the relative simplicity of these smaller pieces as part of an iterative process. For algorithms that use first-order (i.e. gradient) information, operator splitting provides the unifying mathematical framework. In recent times, there […]
Description: Slow viscous flows with interfaces are seen in many different industrial and natural processes including optical fibre and window glass fabrication, chemical etching, lava flows, landslides, underground salt plumes, the tear film on the eye, solidification, and more. Mathematical modelling can identify and quantify important industrial control parameters, enable solution of difficult inverse problems, […]
Description: Integrable systems have long been used to study the global properties of surfaces arising from variational problems. More recently, integrable discretisations of the smooth theory have been developed and the cross-fertilisation of ideas between the smooth and discrete theories has been extremely fruitful for both. Originally the smooth theory provided motivation for the discrete […]
