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In this paper, we establish sublinear and linear convergence of fixed point iterations generated by averaged operators in a Hilbert space. Our results are achieved under a bounded H\"older regularity assumption which generalizes the…

Optimization and Control · Mathematics 2018-08-16 Jonathan M. Borwein , Guoyin Li , Matthew K. Tam

We introduce the notion of consistent error bound functions which provides a unifying framework for error bounds for multiple convex sets. This framework goes beyond the classical Lipschitzian and H\"olderian error bounds and includes…

Optimization and Control · Mathematics 2023-10-20 Tianxiang Liu , Bruno F. Lourenço

For the Tikhonov regularization of ill-posed nonlinear operator equations, convergence is studied in a Hilbert scale setting. We include the case of oversmoothing penalty terms, which means that the exact solution does not belong to the…

Numerical Analysis · Mathematics 2020-02-03 Bernd Hofmann , Robert Plato

A nonstandard proof of a generalization of Karamata uniform convergence theorem for slowly varying functions is presented. Properties of a related operator $\mathcal{L}$ and its connection with slowly varying functions are discussed.

General Mathematics · Mathematics 2022-11-24 Žarko Mijajlović , Danijela Branković

We prove a general quantitative theorem on the asymptotic behavior of stochastic quasi-Fej\'er monotone sequences in a broad metric context. Concretely, our result explicitly constructs a rate of convergence for such process, both in mean…

Optimization and Control · Mathematics 2026-05-08 Nicholas Pischke , Thomas Powell

Despite significant recent advances in the regularity theory for obstacle problems with integro-differential operators, some fundamental questions remained open. On the one hand, there was a lack of understanding of parabolic problems with…

Analysis of PDEs · Mathematics 2023-06-29 Alessio Figalli , Xavier Ros-Oton , Joaquim Serra

This paper provides and extends second-order versions of several fundamental theorems on first-order regularly varying functions such as Karamata's theorem/representation and Tauberian's theorem. Our results are used to establish…

Probability · Mathematics 2025-02-10 Ulrich Horst , Wei Xu

Quasi-convex optimization acts a pivotal part in many fields including economics and finance; the subgradient method is an effective iterative algorithm for solving large-scale quasi-convex optimization problems. In this paper, we…

Optimization and Control · Mathematics 2019-10-25 Yaohua Hu , Jiawen Li , Carisa Kwok Wai Yu

In this paper, we develop a regularized higher-order Taylor based method for solving composite (e.g., nonlinear least-squares) problems. At each iteration, we replace each smooth component of the objective function by a higher-order Taylor…

Optimization and Control · Mathematics 2025-03-05 Yassine Nabou , Ion Necoara

We study the higher H\"older regularity of local weak solutions to a class of nonlinear nonlocal elliptic equations with kernels that satisfy a mild continuity assumption. An interesting feature of our main result is that the obtained…

Analysis of PDEs · Mathematics 2021-01-19 Simon Nowak

We study the convergence properties of a general inertial first-order proximal splitting algorithm for solving nonconvex nonsmooth optimization problems. Using the Kurdyka--\L ojaziewicz (KL) inequality we establish new convergence rates…

Optimization and Control · Mathematics 2016-09-14 Patrick R. Johnstone , Pierre Moulin

In this paper, we develop new first-order method for composite non-convex minimization problems with simple constraints and inexact oracle. The objective function is given as a sum of "`hard"', possibly non-convex part, and "`simple"'…

Optimization and Control · Mathematics 2017-03-28 Pavel Dvurechensky

Kernel-based quadrature rules are becoming important in machine learning and statistics, as they achieve super-$\sqrt{n}$ convergence rates in numerical integration, and thus provide alternatives to Monte Carlo integration in challenging…

Machine Learning · Statistics 2016-10-31 Motonobu Kanagawa , Bharath K. Sriperumbudur , Kenji Fukumizu

In [19], a general, inexact, efficient proximal quasi-Newton algorithm for composite optimization problems has been proposed and a sublinear global convergence rate has been established. In this paper, we analyze the convergence properties…

Numerical Analysis · Computer Science 2017-10-18 Hiva Ghanbari , Katya Scheinberg

We introduce regularity notions for averaged nonexpansive operators. Combined with regularity notions of their fixed point sets, we obtain linear and strong convergence results for quasicyclic, cyclic, and random iterations. New convergence…

Optimization and Control · Mathematics 2014-02-25 Heinz H. Bauschke , Dominikus Noll , Hung M. Phan

We show the existence of some special coordinate systems for expressing maps with branch points. These coordinates allow obtaining an explicit representation formula of branch immersions and understanding the regularity of some fundamental…

Differential Geometry · Mathematics 2024-08-06 Tito Medina

We consider perturbed nonlinear ill-posed equations in Hilbert spaces, with operators that are monotone on a given closed convex subset. A simple stable approach is Lavrentiev regularization, but existence of solutions of the regularized…

Numerical Analysis · Mathematics 2018-06-05 Robert Plato , Bernd Hofmann

Despite the broad use of fixed-point iterations throughout applied mathematics, the optimal convergence rate of general fixed-point problems with nonexpansive nonlinear operators has not been established. This work presents an acceleration…

Optimization and Control · Mathematics 2022-06-28 Jisun Park , Ernest K. Ryu

This paper is a continuation to the study of generalized quasi contractive operators, essentially due to Akhtar et al. [A multi-step implicit iterative process for common fixed points of generalized C^{q}-operators in convex metric spaces,…

Functional Analysis · Mathematics 2018-02-28 Zahid Akhtar , Muhammad Aqeel Ahmad Khan

This paper deals with a modifed iterative projection method for approximating a solution of hierarchical fixed point problems for nearly nonexpansive mappings. Some strong convergence theorems for the proposed method are presented under…

Functional Analysis · Mathematics 2014-03-17 Ibrahim Karahan , Murat Ozdemir
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