Complexity of multilinear problems in the worst case setting
β Scribed by Tomasz Jackowski
- Publisher
- Elsevier Science
- Year
- 1990
- Tongue
- English
- Weight
- 892 KB
- Volume
- 6
- Category
- Article
- ISSN
- 0885-064X
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
We study the worst case complexity of solving problems for which information is partial and contaminated by random noise. It is well known that if information is exact then adaption does not help for solving linear problems, i.e., for approximating linear operators over convex and symmetric sets. On
## Abstract We believe that discontinuous linear information is never more powerful than continuous linear information for approximating continuous operators. We prove such a result in the worst case setting. In the randomized setting we consider compact linear operators defined between Hilbert spa