Connections between Optimization, Learning and Control: Past, Present and Future

As part of the summer school "Foundations and mathematical guarantees of data-driven control", we would like to announce the talk by Prof. Stephen Wright entitled "Connections between Optimization, Learning and Control: Past, Present and Future".

Abstract: Optimization, learning, and control are interconnected disciplines, enriching each other with the complementary perspectives that they provide on many problems and issues. We start by tracing the historical engagement of optimization with control and learning, leading to the present situation in which optimization methods play a central role in such areas as deep neural networks, low-rank matrix problems, and model predictive control. We present some recent results on the use of neural networks in process control, and discuss the ways in which control and learning have influenced core optimization research. Finally we speculate on some possible future arenas of engagement between these areas.