Preprints

[1]	R. Gribonval, T. Mary & E. Riccietti, Optimal quantization of rank-one matrices in floating-point arithmetic-with applications to butterfly factorizations, preprint, 2023.

International conferences with proceedings

[1]	Q.T. Le, E. Riccietti & R. Gribonval, Does a sparse ReLU network training problem always admit an optimum?, NeurIPS, 2023.
[2]	E.Riccietti. G. Lauga, Multilevel FISTA for Image Restoration, ICASSP, 2023.
[3]	L. Zheng, G. Puy, E. Riccietti, P. Pérez & R. Gribonval, Self-supervised learning with rotation-invariant kernels, ICLR, 2023.
[4]	QT. Le, L. Zheng, E. Riccietti & R. Gribonval, Fast Learning of Fast Transforms, with Guarantees in ICASSP, 2022.
[5]	E. Riccietti, S. Bellavia & S. Sello, Numerical Methods for Optimization Problems Arising in Energetic Districts in Progress in Industrial Mathematics at ECMI 2016, 2016.

Journal Articles

[1]	S. Gratton, V. Mercier, E. Riccietti & Ph.L. Toint, A block-coordinate approach of multi-level optimization with an application to physics-informed neural networks, Computational Optimization and Applications, pages 1-33, Springer, 2024.
[2]	G. Lauga, E. Riccietti, N. Pustelnik & P. Gonçalves, IML FISTA: A Multilevel Framework for Inexact and Inertial Forward-Backward. Application to Image Restoration, SIAM Journal on Imaging Sciences, 17(3):1347-1376, SIAM, 2024.
[3]	A. Gonon, N. Brisebarre, R. Gribonval & E. Riccietti, Approximation speed of quantized vs. unquantized ReLU neural networks and beyond, IEEE Transactions on Information Theory, 2023.
[4]	L. Zheng, E. Riccietti & R. Gribonval, Efficient Identification of Butterfly Sparse Matrix Factorizations, SIAM Journal on Mathematics of Data Science, 2023.
[5]	QT. Le, E. Riccietti & R. Gribonval, Spurious Valleys, NP-hardness, and Tractability of Sparse Matrix Factorization With Fixed Support, SIAM Journal on Matrix Analysis and Applications, 44(2):503-529, SIAM, 2023.
[6]	A.L. Custodio, Y. Diouane, R. Garmanjani & E. Riccietti, Worst-case complexity bounds of directional direct-search methods for multiobjective optimization, Journal of Optimization Theory and Applications, 188(1):1-21, 2020.
[7]	H. Calandra, S. Gratton, E. Riccietti & X. Vasseur, On iterative solution of the extended normal equations, SIAM Journal on Matrix Analysis and Applications, 41(4):1571-1589, 2020.
[8]	H. Calandra, S. Gratton, E. Riccietti & X. Vasseur, On a multilevel Levenberg-Marquardt method for the training of artificial neural networks and its application to the solution of partial differential equations, Optimization Methods and Software, 2020.
[9]	H. Calandra, S. Gratton, E. Riccietti & X. Vasseur, On high-order multilevel optimization strategies, SIAM Journal on Optimization, 31(1):307-330, 2020.
[10]	S. Bellavia, M. Donatelli & E. Riccietti, An inexact non stationary Tikhonov procedure for large-scale nonlinear ill-posed problems, Inverse Problems, 36(9), 2020.
[11]	S. Bellavia, S. Gratton & E. Riccietti, A Levenberg-Marquardt method for large nonlinear least-squares problems with noisy functions and gradients, Numerische Mathematik, 140(3):791-825, Springer, 2018.
[12]	S. Bellavia & E. Riccietti, On an elliptical trust-region procedure for ill-posed nonlinear least squares problems, Journal of Optimization Theory and Applications, 158(3):824-859, 2018.
[13]	E. Riccietti, S. Bellavia & S. Sello, Sequential Linear Programming and Particle Swarm Optimization for the optimization of energy districts, Engineering Optimization, pages 1-17, Taylor & Francis, 2018.
[14]	E. Riccietti, J. Bellucci, M. Checcucci, M. Marconcini & A. Arnone, Support Vector Machine classification applied to the parametric design of centrifugal pumps, Engineering Optimization, pages 1-21, Taylor & Francis, 2017.
[15]	S. Bellavia, B. Morini & E. Riccietti, On an adaptive regularization for ill-posed nonlinear systems and its trust-region implementation, Computational Optimization and Applications, 64(1):1-30, Springer, 2016.

French conferences with proceedings

[1]	R. Gribonval, T. Mary & E. Riccietti, Scaling is all you need: quantization of butterfly matrix products via optimal rank-one quantization, GRETSI, 2023.
[2]	L. Zheng, G. Puy, E. Riccietti, Perez. P. & R. Gribonval, Factorisation butterfly d’une matrice permuté par partitionnement spectral alterné, GRETSI, 2023.
[3]	G. Lauga, E. Riccietti, N. Pustelnik & P. Gonçalves, Méthodes multi-niveaux pour la restauration d'images hyperspectrales, GRETSI 2023, 2023.
[4]	E.Riccietti. G. Lauga, Méthodes proximales multi-niveaux pour la restauration d'images, GRETSI, 2022.

Thesis

[1]	E. Riccietti, Numerical methods for optimization problems: an application to energetic districts Master thesis, 2014.
[2]	E. Riccietti, Levenberg-Marquardt methods for the solution of noisy nonlinear least squares problems PhD thesis, 2018.