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Pubblicazioni

Chambolle-Pock's Primal-Dual Method with Mismatched Adjoint

Autori: Dirk A. Lorenz and Felix Schneppe
Pubblicato in: 2022
Editore: ArXiv

Convergence of an Asynchronous Block-Coordinate Forward-Backward Algorithm for Convex Composite Optimization

Autori: Cheik Traoré, Saverio Salzo, Silvia Villa
Pubblicato in: 2021
Editore: ArXiv
DOI: 10.48550/arxiv.2201.05498

Finding global solutions for a class of possibly nonconvex QCQP problems through the S-lemma

Autori: Ewa M. Bednarczuk, Giovanni Bruccola
Pubblicato in: 2022
Editore: ArXiv
DOI: 10.48550/arxiv.2206.00618

Efficiency of higher-order algorithms for minimizing general composite optimization

Autori: Yassine Nabou and Ion Necoara
Pubblicato in: 2022
Editore: AirXiv

Efficiency of stochastic coordinate proximal gradient methods on nonseparable composite optimization

Autori: Necoara, I.; Chorobura, F.
Pubblicato in: Numero 1, 2021
Editore: ArXiv

Random coordinate descent methods for nonseparable composite optimization

Autori: Flavia Chorobura and Ion Necoara
Pubblicato in: 2022
Editore: AirXiv

Fast iterative regularization by reusing data

Autori: Cristian Vega, Cesare Molinari, Lorenzo Rosasco, Silvia Villa
Pubblicato in: 2022
Editore: ArXiv
DOI: 10.48550/arxiv.2204.10131

Weak topology and Opial property in Wasserstein spaces, with applications to Gradient Flows and Proximal Point Algorithms of geodesically convex functionals

Autori: Emanuele Naldi and Giuseppe Savaré,
Pubblicato in: 2021
Editore: AirXiv

A CNC approach for Directional Total Variation

Autori: Gabriele Scrivanti, Émilie Chouzenoux, Jean-Christophe Pesquet
Pubblicato in: 2022
Editore: HAL OPen Science

Cartoon images dataset for total variation parameter learning

Autori: Enis Chenchene, Kristian Bredies, Alireza Hosseini
Pubblicato in: Zenodo, 2022
Editore: CERN
DOI: 10.5281/zenodo.7267053

A variational approach for joint image recovery-segmentation based on spatially varying generalised Gaussian models

Autori: Emilie Chouzenoux, Marie-Caroline Corbineau, Jean-Christophe Pesquet, Gabriele Scrivanti
Pubblicato in: 2022
Editore: HAL Open Science

Extended Randomized Kaczmarz Method for Sparse Least Squares and Impulsive Noise Problems

Autori: Frank Schöpfer, Dirk A Lorenz, Lionel Tondji, and Maximilian Winkler
Pubblicato in: 2022
Editore: ArXiv

Faster Randomized Block Sparse Kaczmarz by Averaging

Autori: Lionel Tondji, Dirk A Lorenz
Pubblicato in: 2022
Editore: AirXiv

Modified projected Gauss-Newton method for constrained nonlinear least-squares: application to power flow analysis

Autori: Y Nabou, L Toma and I Necoara
Pubblicato in: European Control Conference (ECC), 2023, Pagina/e 1-6
Editore: IEEE
DOI: 10.23919/ecc57647.2023.10178179

Coordinate projected gradient descent minimization and its application to orthogonal nonnegative matrix factorization

Autori: Flavia Chorobura, Daniela Lupu, Ion Necoara
Pubblicato in: IEEE 61st Conference on Decision and Control (CDC), 2022, Pagina/e 6929-6934
Editore: IEEE
DOI: 10.1109/cdc51059.2022.9992996

Can random proximal coordinate descent be accelerated on nonseparable convex composite minimization problems?

Autori: Flavia Chorobura, Francois Glineur and Ion Necoara
Pubblicato in: European Control Conference (ECC), 2023
Editore: IEEE
DOI: 10.23919/ecc57647.2023.10178217

A hybrid proximal generalized conditional gradient method and application to total variation parameter learning

Autori: Enis Chenchene, Kristian Bredies, Alireza Hosseini
Pubblicato in: 2023 European Control Conference (ECC), 2022, Pagina/e 322-327
Editore: IEEE
DOI: 10.23919/ecc57647.2023.10178166

GPU-based Implementations of MM Algorithms.Application to Spectroscopy Signal Restoration

Autori: Mouna Gharbi, E. Chouzenoux, J.-C. Pesquet, L. Duval
Pubblicato in: Proceedings of the 29th European Signal Processing Conference, EUSIPCO 2021, Numero 29, 2021, Pagina/e 2094-2098
Editore: Eurasip open library

An accelerated randomized Bregman-Kaczmarz method for strongly convex linearly constraint optimization*

Autori: L. Tondji, D. A. Lorenz and I. Necoara
Pubblicato in: 2023 European Control Conference (ECC), 2023, Pagina/e 1-6
Editore: IEEE
DOI: 10.23919/ecc57647.2023.10178390

Duality for composite optimization problem within the framework of abstract convexity

Autori: Ewa Bednarczuk; The Hung Tran
Pubblicato in: Optimization: A Journal of Mathematical Programming and Operations Research, Numero Volume 72, 2023 - Numero 1, 2023, Pagina/e 37-80, ISSN 0233-1934
Editore: Taylor & Francis
DOI: 10.1080/02331934.2022.2132822

Extended randomized Kaczmarz method for sparse least squares and impulsive noise problems

Autori: Frank Schöpfer, Dirk A. Lorenz, Lionel Tondji, Maximilian Winkler
Pubblicato in: Linear Algebra and Applications, Numero 652, 2022, Pagina/e 132–154, ISSN 0024-3795
Editore: Elsevier BV
DOI: 10.1016/j.laa.2022.07.003

Efficiency of higher-order algorithms for minimizing composite functions

Autori: Y. Nabou, I. Necoara
Pubblicato in: Computational Optimization and Applications, 2023, ISSN 1573-2894
Editore: Springer Netherlands
DOI: 10.1007/s10589-023-00533-9

Degenerate preconditioned proximal point algorithms

Autori: Kristian Bredies, Enis Chenchene, Dirk Lorenz, Emanuale Naldi
Pubblicato in: SIAM Journal on Optimization, Numero 10526234, 2022, Pagina/e 2376-2401, ISSN 1052-6234
Editore: Society for Industrial and Applied Mathematics
DOI: 10.1137/21m1448112

On extreme points and representer theorems for the Lipschitz unit ball on finite metric spaces

Autori: Kristian Bredies, Jonathan Chirinos Rodriguez, Emanuele Naldi
Pubblicato in: Archiv der Mathematik, Numero 122(6), 2024, Pagina/e 651-658, ISSN 0003-889X
Editore: Birkhauser Verlag
DOI: 10.1007/s00013-024-01978-y

Sequential convergence of AdaGrad algorithm for smooth convex optimization

Autori: Cheik Traoré, Edouard Pauwels
Pubblicato in: Operations Research Letters, Numero 49/4, 2021, Pagina/e 452-458, ISSN 0167-6377
Editore: Elsevier BV
DOI: 10.1016/j.orl.2021.04.011

Graph and distributed extensions of the Douglas-Rachford method

Autori: Kristian Bredies, Enis Chenchene, Emanuele Naldi
Pubblicato in: SIAM Journal on Optimization, Numero 34(2), 2024, Pagina/e 1569-1594, ISSN 1052-6234
Editore: Society for Industrial and Applied Mathematics
DOI: 10.1137/22m1535097

Linearly convergent adjoint free solution of least squares problems by random descent

Autori: Dirk A. Lorenz, Felix Schneppe, and Lionel Tondji
Pubblicato in: Inverse Problems, Numero Volume 39, Number 12, 2023, ISSN 0266-5611
Editore: Institute of Physics Publishing
DOI: 10.1088/1361-6420/ad08ed

On global solvability of a class of possibly nonconvex QCQP problems in Hilbert spaces

Autori: Ewa M. Bednarczuk, Giovanni Bruccola
Pubblicato in: Optimisation, 2023, ISSN 0233-1934
Editore: Taylor & Francis
DOI: 10.1080/02331934.2023.2281640

Random Activations in Primal-Dual Splittings for Monotone Inclusions with a Priori Information

Autori: Luis Briceño-Arias, Julio Deride, Cristian Vega
Pubblicato in: Journal of Optimization Theory and Applications volume 192, issue 1, pages 56–81 (2022), 2022, ISSN 0022-3239
Editore: Kluwer Academic/Plenum Publishers
DOI: 10.1007/s10957-021-01944-6

In Vivo Myelin Water Quantification Using Diffusion–Relaxation Correlation MRI: A Comparison of 1D and 2D Methods

Autori: Sebastian Endt, Maria Engel, Emanuele Naldi, Rodolfo Assereto, Malwina Molendowska, Lars Mueller, Claudio Mayrink Verdun, Carolin M. Pirkl, Marco Palombo, Derek K. Jones, Marion I. Menzel
Pubblicato in: Applied Magnetic Resonance, 2023, ISSN 0937-9347
Editore: Springer Verlag
DOI: 10.1007/s00723-023-01584-1

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