Emanuele Naldi

Research interests: Splitting algorithms - Optimal transport - Optimization in spaces of measures - Distributed optimization - Functional analysis for Neural Networks - Plug-and-Play methods

People I have collaborated with: Simone Di Marino - Silvia Villa - Giuseppe Savaré - Dirk Lorenz - Kristian Bredies - Enis Chenchene - Pontus Giselsson - Sara Farinelli - Hippolyte Labarrière - Maicon Marques Alves - Anton Akermann - Felix Schneppe - Jonathan Chirinos Rodríguez - Cesare Molinari - Jannis Marquardt - Francesca Bartolucci - Marcello Carioni - José A. Iglesias - Yury Korolev - Stefano Vigogna - Rodolfo Assereto - Sebastian Endt - Marion I. Menzel

List of Journals: SIAM Journal on Mathematical Analysis - SIAM Journal on Optimization - Computational Optimization and Applications - Atti della Accademia Nazionale dei Lincei - Optimization - Archiv der Mathematik - Applied Magnetic Resonance

Publications in peer-reviewed scientific journals

The Influence of an Adjoint Mismatch on the Primal-Dual Douglas-Rachford Method (with Felix Schneppe). Optimization 1–38 (2026)
A Lipschitz spaces view of infinitely wide shallow neural networks (with Francesca Bartolucci, Marcello Carioni, José A. Iglesias, Yury Korolev, Stefano Vigogna). SIAM Journal on Mathematical Analysis 58 (3), 2786-2828 (2026)
A general framework for inexact splitting algorithms with relative errors and applications to Chambolle-Pock and Davis-Yin methods (with M. Marques Alves, Dirk A. Lorenz). Computational Optimization and Applications (2025)
Graph and distributed extensions of the Douglas–Rachford method (with Kristian Bredies and Enis Chenchene). SIAM Journal on Optimization 34 (2), 1569-1594 (2024)
On extreme points and representer theorems for the Lipschitz unit ball on finite metric spaces (with Kristian Bredies and Jonathan Chirinos-Rodriguez). Archiv der Mathematik, 1-8 (2024)
The Degenerate Variable Metric Proximal Point Algorithm and Adaptive Stepsizes for Primal-Dual Douglas-Rachford (with Dirk A. Lorenz, Jannis Marquardt). Optimization, 1-27 (2024)
In Vivo Myelin Water Quantification Using Diffusion–Relaxation Correlation MRI: A Comparison of 1D and 2D Methods (with Sebastian Endt, Rodolfo Assereto, Marion I. Menzel et al.). Applied Magnetic Resonance (2023)
Degenerate Preconditioned Proximal Point algorithms (with Kristian Bredies, Enis Chenchene and Dirk Lorenz). SIAM Journal on Optimization, vol. 32, no. 3, pp. 2376–2401 (2022)
Weak topology and Opial property in Wasserstein spaces, with applications to gradient flows and proximal point algorithms of geodesically convex functionals (with Giuseppe Savaré). Atti Accad. Naz. Lincei Cl. Sci. Fis. Mat. Natur. 32, 725-750 (2021)

Preprints

On the stability of proximal operators in Wasserstein spaces under different notions of convexity (with Simone Di Marino and Sara Farinelli). arXiv preprint (2026)
Convergence of zeroth-order proximal point algorithms in the high-temperature regime (with Hippolyte Labarrière, Cesare Molinari and Silvia Villa). arXiv preprint (2026)
Splitting the Forward-Backward Algorithm: A Full Characterization (with Anton Åkerman, Enis Chenchene and Pontus Giselsson). arXiv preprint (2025)
Inexact JKO and proximal-gradient in Wasserstein spaces (with Simone Di Marino and Silvia Villa). arXiv preprint (2025)
Learning Firmly Nonexpansive Operators (with Kristian Bredies and Jonathan Chirinos Rodriguez). arXiv preprint (2024)

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