A key question in many low-rank problems throughout optimization, machine learning, and statistics is to characterize the convex hulls of simple low-rank sets and judiciously apply these convex hulls ...

Submodular function optimisation has emerged as a cornerstone of contemporary algorithm design, offering a powerful framework to address a broad range of combinatorial problems characterised by the ...

Real-world optimization problems often require an external “modeling engine” that computes fitnesses or data that are then input to an objective function. These programs often have much longer ...