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A numerical algorithm for attaining the Chebyshev bound in optimal learning
- Publication Year :
- 2023
-
Abstract
- Given a compact subset of a Banach space, the Chebyshev center problem consists of finding a minimal circumscribing ball containing the set. In this article we establish a numerically tractable algorithm for solving the Chebyshev center problem in the context of optimal learning from a finite set of data points. For a hypothesis space realized as a compact but not necessarily convex subset of a finite-dimensional subspace of some underlying Banach space, this algorithm computes the Chebyshev radius and the Chebyshev center of the hypothesis space, thereby solving the problem of optimal recovery of functions from data. The algorithm itself is based on, and significantly extends, recent results for near-optimal solutions of convex semi-infinite problems by means of targeted sampling, and it is of independent interest. Several examples of numerical computations of Chebyshev centers are included in order to illustrate the effectiveness of the algorithm.<br />22 pages, 16 figures
- Subjects :
- Signal Processing (eess.SP)
FOS: Computer and information sciences
Computer Science - Machine Learning
Optimization and Control (math.OC)
FOS: Mathematics
FOS: Electrical engineering, electronic engineering, information engineering
Systems and Control (eess.SY)
Electrical Engineering and Systems Science - Signal Processing
Mathematics - Optimization and Control
Electrical Engineering and Systems Science - Systems and Control
Machine Learning (cs.LG)
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....55a58e1e55cda718117a718fe9ac0dd2