Abstract
We study optimal algorithms and optimal information for an average case model. This is done for linear problems in a separable Hilbert space equipped with a probability measure. We show, in particular, that for any measure a (linear) spline algorithm is optimal among linear algorithms. The spline algorithm is defined in terms of the covariance operator of the measure. We provide a condition on the measure which guarantees that the spline algorithm is optimal among all algorithms. The problem of optimal information is also solved.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.