Conference Proceedings

-  G. Franchini, F. Porta, V. Ruggiero, I. Trombini, L. Zanni,  Line Search Stochastic Gradient Algorithm with a-priori rule for monitoring the control of the variance, LNCS NUMTA  2023 Conference Proceeding, in press.

-  G. Franchini, F. Porta, V. Ruggiero, I. Trombini, L. Zanni,  Diagonal Barzilai-Borwein Rules in Stochastic Gradient-Like Methods. In: Dorronsoro, B., Chicano, F., Danoy, G., Talbi, EG. (eds) Optimization and Learning. OLA 2023. Communications in Computer and Information Science, vol 1824. Springer, Cham. https://doi.org/10.1007/978-3-031-34020-8_2 (2023)

- G. Franchini , V. Ruggiero, I. Trombini, Thresholding Procedure via Barzilai-Borwein Rules for the Steplength Selection in Stochastic Gradient Methods. In: Nicosia G. et al. (eds) Machine Learning, Optimization, and Data Science. LOD 2021. Lecture Notes in Computer Science, vol 13164. Springer, Cham. https://doi.org/10.1007/978-3-030-95470-3_21, (2022) 

- G. Franchini, V. Ruggiero, L. Zanni, Steplength and Mini-batch Size Selection in Stochastic Gradient Methods, In: Nicosia G. et al. (eds) Machine Learning, Optimization, and Data Science. LOD 2020. Lecture Notes in Computer Science, vol 12566. Springer, Cham. https://doi.org/10.1007/978-3-030-64580-9_22 (2021)

- S. Crisci, F. Porta, V. Ruggiero, L. Zanni, A Limited Memory Gradient Projection Method for Box-Constrained Quadratic Optimization Problems. In: Sergeyev Y., Kvasov D. (eds) Numerical Computations: Theory and Algorithms. NUMTA 2019. Lecture Notes in Computer Science, vol 11973, (2020). Springer, Cham. doi.org/10.1007/978-3-030-39081-5_15

- G. Franchini, V. Ruggiero, L. Zanni, On the Steplength Selection in Stochastic Gradient Methods. In: Sergeyev Y., Kvasov D. (eds) Numerical Computations: Theory and Algorithms. NUMTA 2019. Lecture Notes in Computer Science, vol 11973 (2020), Springer, Cham . doi.org/10.1007/978-3-030-39081-5_17

- D. Lazzaro, E. Loli Piccolomini, V. Ruggiero, F. Zama, A fast subgradient algorithm in image super-resolution, Proceeding NCMIP, Journal of Physics: Conference Series, Volume 904, Issue 1, 22 October 2017, Article number 0120092017.

- R. Zanella, V. Ruggiero, M. Zanetti, A Parallel Approach for Image Segmentation by Numerical Minimization of a Second-Order Functional, AIP Conference Proceedings 1776, 090035 (2016); dx.doi.org/10.1063/1.4965399

- D. di Serafino, V. Ruggiero, G. Toraldo, L. Zanni, A Note on Spectral Properties of Some Gradient Methods, AIP Conference Proceedings 1776, 040003 (2016); dx.doi.org/10.1063/1.4965315

- V. L. Coli, V. Ruggiero, L. Zanni, Scaled First–Order Methods for a Class of Large–Scale Constrained Least Squares Problems, AIP Conference Proceedings 1776, 040002 (2016); dx.doi.org/10.1063/1.4965314

- A. Benfenati, , V. Ruggiero, Image regularization for Poisson data, Journal of Physics:Conference Series 657 (2015) 012011, DOI:10.1088/1742-6596/657/1/012011

· S. Bonettini, A. Benfenati, V. Ruggiero, Primal-dual first order methods for total variation image restoration in presence of Poisson noise, IEEE International Conference on Image Processing, 2014. DOI:10.1109/ICIP.2014.7025844. pp.4156-4160

· S. Bonettini, V. Ruggiero, On On the uniqueness of the solution of image reconstruction problems with Poisson data, AIP Conference Proc., 1281, 1803-1806, (2010).

· E. Galligani, V. Ruggiero, Implementation of Splitting Methods for Solving Block Tridiagonal Linear Systems on Transputers, Proceedings of Euromicro PDP, IEEE Computer Society Publishers, Los Alamitos, 409-415 (1995).

· Galligani, E. Loli Piccolomini, V. Ruggiero, A Substructuring Method for Solving The Image Restoration Problem on A Multiprocessor System, Proceedings of SMS 94 TPE, Mosca, 435-444 (1994).

· E. Galligani, V. Ruggiero, Analysis of Splitting Parallel Methods for Solving Block Tridiagonal Linear Systems, Proceedings of SMS 94 TPE, Mosca, 406-416 (1994).

· G. Casciola, V. Ruggiero, Tecniche e metodi per la realizzazione di libri elettronici, Atti del Convegno Internazionale ANTEM, 263-280, Bologna (1985).