Optimization and sampling problems over group orbits and their convex hulls, called orbitopes, capture various important problems in computer science, mathematics, and physics. For instance, the problem of finding minimum norm vectors in orbits has connections with scaling problems, linear programming, and testing algebraic identities; and the set of density matrices, central to semidefinite programming and quantum computing, is an orbitope. It turns out that several orbit problems, while not convex, are geodesically convex optimization problems. There are also deep connections between orbits/orbitopes and polytopes. Recent works have developed algorithms for a number of problems that leverage these connections and, crucially, the symmetry of the problems.
This workshop will focus on algorithms for computational problems related to orbits and orbitopes, and explore connections of these objects with theoretical computer science, discrete optimization, quantum physics, statistics, mathematics, and machine learning.
This event will be held in-person and virtually.
Given current public health directives from state, local, and university authorities, all participants in Simons Institute events must be prepared to demonstrate proof of full vaccination: a vaccination card or photo of the card along with a valid photo ID, or a green Campus Access Badge via the UC Berkeley Mobile app (additional details regarding proof of vaccination can be found here).
If you require accommodation for communication, please contact our Access Coordinator at simonsevents [at] berkeley.edu with as much advance notice as possible.
If you are interested in joining this workshop, please see the Participate page.
Registration is required to attend this workshop. Space may be limited, and you are advised to register early. To submit your name for consideration, please register and await confirmation of your acceptance before booking your travel.