Abstract
In this paper we provide implementable methods for solving nondifferentiable convex optimization problems. A typical method minimizes an approximate Moreau-Yosida regularization using a quasi-Newton technique with inexact function and gradient values which are generated by a finite inner bundle algorithm. For a BFGS bundle-type method global and superlinear convergence results for the outer iteration sequence are obtained.
| Original language | English |
|---|---|
| Pages (from-to) | 583-603 |
| Number of pages | 21 |
| Journal | SIAM Journal on Optimization |
| Volume | 8 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 1 Jan 1998 |
| Externally published | Yes |
Keywords
- Bundle method
- Moreau-Yosida regularization
- Quasi-Newton method
- Superlinear convergence
ASJC Scopus subject areas
- Software
- Theoretical Computer Science
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