Inexact proximal Newton methods in Hilbert spaces
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
Abstract
We consider proximal Newton methods with an inexact computation of update steps. To this end, we introduce two inexactness criteria which characterize sufficient accuracy of these update step and with the aid of these investigate global convergence and local acceleration of our method. The inexactness criteria are designed to be adequate for the Hilbert space framework we find ourselves in while traditional inexactness criteria from smooth Newton or finite dimensional proximal Newton methods appear to be inefficient in this scenario. The performance of the method and its gain in effectiveness in contrast to the exact case are showcased considering a simple model problem in function space.
Details
Original language | English |
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Pages (from-to) | 1-37 |
Number of pages | 37 |
Journal | Computational optimization and applications |
Volume | 87 |
Issue number | 1 |
Publication status | Published - Jan 2024 |
Peer-reviewed | Yes |
Keywords
ASJC Scopus subject areas
Keywords
- Inexactness, Non-smooth optimization, Optimization in Hilbert space, Proximal Newton