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
Sharp adaptation for inverse problems with random noise
β Scribed by Laurent Cavalier; Alexandre Tsybakov
- Publisher
- Springer
- Year
- 2002
- Tongue
- English
- Weight
- 225 KB
- Volume
- 123
- Category
- Article
- ISSN
- 1432-2064
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