Concrete convergence rates for common fixed point problems under Karamata regularity
Tianxiang Liu, Bruno F. Louren\c{c}o

TL;DR
This paper introduces Karamata regular operators to derive explicit convergence rates for fixed point algorithms, extending beyond H"olderian assumptions and applying to non-H"olderian problems involving exponential and logarithmic data.
Contribution
It develops a new framework using Karamata regularity and regularly varying functions to obtain concrete convergence rates in non-H"olderian settings, including intermediate rates and connections to o-minimal geometry.
Findings
Derived explicit convergence rates involving Lambert W function.
Extended convergence analysis beyond H"olderian assumptions.
Linked Karamata regularity to o-minimal definable operators.
Abstract
We introduce the notion of Karamata regular operators, which is a notion of regularity that is suitable for obtaining concrete convergence rates for common fixed point problems. This provides a broad framework that includes, but goes beyond, H\"olderian error bounds and H\"older regular operators. By concrete, we mean that the rates we obtain are explicitly expressed in terms of a function of the iteration number instead, of say, a function of the iterate . While it is well-known that under H\"olderian-like assumptions many algorithms converge linearly/sublinearly (depending on the exponent), little it is known when the underlying problem data does not satisfy H\"olderian assumptions, which may happen if a problem involves exponentials and logarithms. Our main innovation is the usage of the theory of regularly varying functions which we showcase by obtaining concrete…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsFixed Point Theorems Analysis · Optimization and Variational Analysis
