Inertial Krasnoselskii-Mann Iterations
Not on the map. Why?
Abstract (arXiv)
We establish the weak convergence of inertial Krasnoselskii-Mann iterations towards a common fixed point of a family of quasi-nonexpansive operators, along with estimates for the non-asymptotic rate at which the residuals vanish. Strong and linear convergence are obtained in the quasi-contractive setting. In both cases, we highlight the relationship with the non-inertial case, and show that passing from one regime to the other is a continuous process in terms of the hypotheses on the parameters. Numerical illustrations are provided for an inertial primal-dual method and an inertial three-operator splitting algorithm, whose performance is superior to that of their non-inertial counterparts.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Oct 2022.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2024: 1; 2025: 2; 2026: 2.
5 papers.
- 2024Gradient-free Decoder Inversion in Latent Diffusion Modelscited by 5
- 2025Non-Expansive Mappings in Two-Time-Scale Stochastic Approximation: Finite-Time Analysiscited by 3
- 2026Learning to accelerate Krasnosel'skii-Mann fixed-point iterations with guaranteescited by 2
- 2025Inertial Quadratic Majorization Minimization with Application to Kernel Regularized Learningcited by 0
- 2026Stochastic Inertial Krasnosel'skii-Mann Iteration Achieves Near-Optimal Sample Complexitycited by 0
- 2026Stochastic Inertial Krasnosel'skii-Mann Iteration Achieves Near-Optimal Sample Complexity22 Sep 2026
- 2026Learning to accelerate Krasnosel'skii-Mann fixed-point iterations with guarantees12 Jan 2026
- 2025Inertial Quadratic Majorization Minimization with Application to Kernel Regularized Learning6 Jul 2025
- 2025Non-Expansive Mappings in Two-Time-Scale Stochastic Approximation: Finite-Time Analysis18 Jan 2025
- 2024Gradient-free Decoder Inversion in Latent Diffusion Models27 Sep 2024