![]() |
![]() |
University of Birmingham > Talks@bham > Optimisation and Numerical Analysis Seminars > Geometry of First-order Proximal Splitting Methods and Beyond
Geometry of First-order Proximal Splitting Methods and BeyondAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Sergey Sergeev. First-order proximal splitting methods are widely used in many fields through science and engineering, such as compressed sensing, signal/image processing, data science, machine learning and statistics, to name a few. Over the past decades, motivated by problems arising from these fields, modern optimisation has experienced a tremendous growth. Spectacular progress has been made in people’s understanding of optimisation problems and, in particular, of convex programming which is suitable for a wide spectrum of important problems in science and engineering. In this talk, I will present a geometric perspective of first-order methods when applied to non-smooth optimisation. Based on Riemannian geometry, several geometric characterisations of first-order methods are provided, from which we can design generic frameworks for the local linear convergence and adaptive acceleration of first-order methods. Concrete examples from inverse problems, image processing and machine learning will be used to demonstrate the state-of-the-art performance of the obtained results. This talk is part of the Optimisation and Numerical Analysis Seminars series. This talk is included in these lists:Note that ex-directory lists are not shown. |
Other listsEPS - College Research Teas Nanoscale Physics Seminars Type the title of a new list hereOther talksTBC Cost optimisation of hybrid institutional incentives for promoting cooperation in finite populations The science of the large scale heliosphere and the missions that made it possible Seminar: TBA Seminar: TBA Seminar: TBA |