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Marco Prato
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- affiliation: University of Modena and Reggio Emilia
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2020 – today
- 2024
- [j23]Silvia Bonettini, Marco Prato, Simone Rebegoldi:
A new proximal heavy ball inexact line-search algorithm. Comput. Optim. Appl. 88(2): 525-565 (2024) - [j22]Luca Calatroni, Marco Donatelli, Serena Morigi, Marco Prato, Matteo Santacesaria:
Guest Editorial JMIV Special Issue SSVM'23. J. Math. Imaging Vis. 66(4): 417-418 (2024) - [i7]Silvia Bonettini, Luca Calatroni, Danilo Pezzi, Marco Prato:
Algorithmic unfolding for image reconstruction and localization problems in fluorescence microscopy. CoRR abs/2403.17506 (2024) - 2023
- [j21]Elena Loli Piccolomini, Marco Prato, Margherita Scipione, Andrea Sebastiani:
CTprintNet: An Accurate and Stable Deep Unfolding Approach for Few-View CT Reconstruction. Algorithms 16(6): 270 (2023) - [j20]Carmelo Scribano, Danilo Pezzi, Giorgia Franchini, Marco Prato:
Denoising Diffusion Models on Model-Based Latent Space. Algorithms 16(11): 501 (2023) - [j19]Silvia Bonettini, Marco Prato, Simone Rebegoldi:
A nested primal-dual FISTA-like scheme for composite convex optimization problems. Comput. Optim. Appl. 84(1): 85-123 (2023) - [j18]Silvia Bonettini, Peter Ochs, Marco Prato, Simone Rebegoldi:
An abstract convergence framework with application to inertial inexact forward-backward methods. Comput. Optim. Appl. 84(2): 319-362 (2023) - [j17]Carmelo Scribano, Giorgia Franchini, Marco Prato, Marko Bertogna:
DCT-Former: Efficient Self-Attention with Discrete Cosine Transform. J. Sci. Comput. 94(3): 67 (2023) - [e1]Luca Calatroni, Marco Donatelli, Serena Morigi, Marco Prato, Matteo Santacesaria:
Scale Space and Variational Methods in Computer Vision - 9th International Conference, SSVM 2023, Santa Margherita di Pula, Italy, May 21-25, 2023, Proceedings. Lecture Notes in Computer Science 14009, Springer 2023, ISBN 978-3-031-31974-7 [contents] - [i6]Silvia Bonettini, Peter Ochs, Marco Prato, Simone Rebegoldi:
An abstract convergence framework with application to inertial inexact forward-backward methods. CoRR abs/2302.07545 (2023) - 2022
- [j16]Matteo Spallanzani, Gueorgui Mihaylov, Marco Prato, Roberto Fontana:
A fingerprint of a heterogeneous data set. Adv. Data Anal. Classif. 16(3): 617-657 (2022) - [j15]Giorgia Franchini, Micaela Verucchi, Ambra Catozzi, Federica Porta, Marco Prato:
Biomedical Image Classification via Dynamically Early Stopped Artificial Neural Network. Algorithms 15(10): 386 (2022) - [j14]Davide Sapienza, Giorgia Franchini, Elena Govi, Marko Bertogna, Marco Prato:
Deep Image Prior for medical image denoising, a study about parameter initialization. Frontiers Appl. Math. Stat. 8 (2022) - [c8]Silvia Bonettini, Giorgia Franchini, Danilo Pezzi, Marco Prato:
Learning the Image Prior by Unrolling an Optimization Method. EUSIPCO 2022: 952-956 - [i5]Carmelo Scribano, Giorgia Franchini, Marco Prato, Marko Bertogna:
DCT-Former: Efficient Self-Attention with Discrete Cosine Transform. CoRR abs/2203.01178 (2022) - [i4]Silvia Bonettini, Giorgia Franchini, Danilo Pezzi, Marco Prato:
Explainable bilevel optimization: an application to the Helsinki deblur challenge. CoRR abs/2210.10050 (2022) - 2021
- [j13]Silvia Bonettini, Marco Prato, Simone Rebegoldi:
New convergence results for the inexact variable metric forward-backward method. Appl. Math. Comput. 392: 125719 (2021) - [j12]Tatiana A. Bubba, Mathilde Galinier, Matti Lassas, Marco Prato, Luca Ratti, Samuli Siltanen:
Deep Neural Networks for Inverse Problems with Pseudodifferential Operators: An Application to Limited-Angle Tomography. SIAM J. Imaging Sci. 14(2): 470-505 (2021) - [c7]Simone Rebegoldi, Silvia Bonettini, Marco Prato:
A comparison of nested primal-dual forward-backward methods for Poisson image deblurring. ICCSA (Workshops) 2021: 87-92 - 2020
- [j11]Silvia Bonettini, Marco Prato, Simone Rebegoldi:
Convergence of Inexact Forward-Backward Algorithms Using the Forward-Backward Envelope. SIAM J. Optim. 30(4): 3069-3097 (2020) - [c6]Mathilde Galinier, Marco Prato, Emilie Chouzenoux, Jean-Christophe Pesquet:
A Hybrid Interior Point - Deep Learning Approach for Poisson Image Deblurring. MLSP 2020: 1-6 - [i3]Tatiana A. Bubba, Mathilde Galinier, Matti Lassas, Marco Prato, Luca Ratti, Samuli Siltanen:
Deep neural networks for inverse problems with pseudodifferential operators: an application to limited-angle tomography. CoRR abs/2006.01620 (2020)
2010 – 2019
- 2019
- [c5]Marie-Caroline Corbineau, Carla Bertocchi, Emilie Chouzenoux, Marco Prato, Jean-Christophe Pesquet:
Learned Image Deblurring by Unfolding a Proximal Interior Point Algorithm. ICIP 2019: 4664-4668 - [c4]Simone Rebegoldi, Silvia Bonettini, Marco Prato:
Efficient Block Coordinate Methods for Blind Cauchy Denoising. NUMTA(1) 2019: 198-211 - 2018
- [j10]Silvia Bonettini, Marco Prato, Simone Rebegoldi:
A block coordinate variable metric linesearch based proximal gradient method. Comput. Optim. Appl. 71(1): 5-52 (2018) - [i2]Carla Bertocchi, Emilie Chouzenoux, Marie-Caroline Corbineau, Jean-Christophe Pesquet, Marco Prato:
Deep Unfolding of a Proximal Interior Point Method for Image Restoration. CoRR abs/1812.04276 (2018) - 2016
- [j9]Silvia Bonettini, Marco Prato, Simone Rebegoldi:
A cyclic block coordinate descent method with generalized gradient projections. Appl. Math. Comput. 286: 288-300 (2016) - [j8]Silvia Bonettini, Ignace Loris, Federica Porta, Marco Prato:
Variable Metric Inexact Line-Search-Based Methods for Nonsmooth Optimization. SIAM J. Optim. 26(2): 891-921 (2016) - [c3]Lola Bautista, Simone Rebegoldi, Laure Blanc-Féraud, Marco Prato, Luca Zanni, Arturo Plata:
Phase estimation in differential-interference-contrast (DIC) microscopy. ISBI 2016: 136-139 - 2015
- [j7]Anastasia Cornelio, Federica Porta, Marco Prato:
A convergent least-squares regularized blind deconvolution approach. Appl. Math. Comput. 259: 173-186 (2015) - [j6]Federica Porta, Marco Prato, Luca Zanni:
A New Steplength Selection for Scaled Gradient Methods with Application to Image Deblurring. J. Sci. Comput. 65(3): 895-919 (2015) - [j5]Silvia Bonettini, Alessandro Chiuso, Marco Prato:
A Scaled Gradient Projection Method for Bayesian Learning in Dynamical Systems. SIAM J. Sci. Comput. 37(3) (2015) - [c2]Simone Rebegoldi, Silvia Bonettini, Marco Prato:
Application of cyclic block generalized gradient projection methods to poisson blind deconvolution. EUSIPCO 2015: 225-229 - 2014
- [i1]Silvia Bonettini, Alessandro Chiuso, Marco Prato:
A scaled gradient projection method for Bayesian learning in dynamical systems. CoRR abs/1406.6603 (2014) - 2013
- [j4]Marco Prato, Luca Zanni:
A practical use of regularization for supervised learning with kernel methods. Pattern Recognit. Lett. 34(6): 610-618 (2013) - [j3]Silvia Bonettini, Anastasia Cornelio, Marco Prato:
A New Semiblind Deconvolution Approach for Fourier-Based Image Restoration: An Application in Astronomy. SIAM J. Imaging Sci. 6(3): 1736-1757 (2013) - 2011
- [j2]Marco Prato, Stefania Favilla, Luca Zanni, Carlo A. Porro, Patrizia Baraldi:
A regularization algorithm for decoding perceptual temporal profiles from fMRI data. NeuroImage 56(1): 258-267 (2011)
2000 – 2009
- 2009
- [j1]Marco Prato, Michele Piana, A. Gordon Emslie, G. J. Hurford, Eduard P. Kontar, Anna Maria Massone:
A Regularized Visibility-Based Approach to Astronomical Imaging Spectroscopy. SIAM J. Imaging Sci. 2(3): 910-930 (2009) - [c1]Marco Prato, Stefania Favilla, Patrizia Baraldi, Carlo A. Porro, Luca Zanni:
From BOLD-fMRI signals to the prediction of subjective pain perception through a regularization algorithm. EUSIPCO 2009: 2332-2336
Coauthor Index
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last updated on 2024-08-29 20:58 CEST by the dblp team
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