Convex optimisation constitutes a fundamental area in applied mathematics where the objective is to identify the minimum of a convex function subject to a set of convex constraints. This framework ...

The goal of this course is to investigate in-depth and to develop expert knowledge in the theory and algorithms for convex optimization. This course will provide a rigorous introduction to the rich ...

This course discusses basic convex analysis (convex sets, functions, and optimization problems), optimization theory (linear, quadratic, semidefinite, and geometric programming; optimality conditions ...

where \(\mathsf{G}(\cdot)\) is some convex operator and \(\mathcal{F}\) is as set of feasible input distributions. Examples of such an optimization problem include finding capacity in information ...

What if the next new mathematical discovery didn’t come from a human mind, but from an AI? Imagine a machine not just crunching numbers but proposing original solutions to problems that have baffled ...

This paper deals with the packing problem of circles and non-convex polygons, which can be both translated and rotated into a strip with prohibited regions. Using the Ф-function technique, a ...

This is a preview. Log in through your library . Abstract Sliced inverse regression is a popular tool for sufficient dimension reduction, which replaces covariates with a minimal set of their linear ...

Nicolò Bernardini, Edoardo Ciccarelli, Nicola Baresi, Roberto Armellin (2023)SUCCESSIVE CONVEX PROGRAMMING FOR HIGH-ORDER GUIDANCE AND NAVIGATION OF SATELLITES, In: Proceedings of the 2023 AAS/AIAA ...