How good is random information? – Approximation in the Hilbert space setting

Description

To find optimal algorithms for numerical problems like function approximation, one has to choose the information optimally, and this might be difficult in practice. Choosing the information functionals as iid random functionals and using the optimal algorithm for the chosen information may be almost as good as using optimal information or may be much worse, depending on the problem setting. We analyse this problem in the Hilbert space setting and give a partial answer in this case about the power of random information. This is joint work with David Krieg and Erich Novak.

Period	02 Jul 2018
Event title	unbekannt/unknown
Event type	Conference
Location	FranceShow on map