Calculus of Variations and Geometric Measure Theory

S. Di Marino - E. Naldi - S. Villa

Inexact JKO and proximal-gradient algorithms in Wasserstein spaces

created by naldi on 21 Mar 2025
modified on 18 Jun 2025

[BibTeX]

Preprint

Inserted: 21 mar 2025
Last Updated: 18 jun 2025

Year: 2025

Abstract:

This paper studies the convergence properties of the inexact Jordan-Kinderlehrer-Otto (JKO) scheme and proximal-gradient algorithm in the context of Wasserstein spaces. The JKO scheme, a widely-used method for approximating solutions to gradient flows in Wasserstein spaces, typically assumes exact solutions to iterative minimization problems. However, practical applications often require approximate solutions due to computational limitations. This work focuses on the convergence of the scheme to minimizers for the underlying functional and addresses these challenges by analyzing two types of inexactness: errors in Wasserstein distance and errors in energy functional evaluations. The paper provides rigorous convergence guarantees under controlled error conditions, demonstrating that weak convergence can still be achieved with inexact steps. The analysis is further extended to proximal-gradient algorithms, showing that convergence is preserved under inexact evaluations.

Keywords: JKO scheme; Inexact optimization; Proximal Gradient; Optimal transport


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