Lossless hyperspectral compression using KLT. - Luca Galli; Saverio Salzo (IGARSS, 2004)

Convergence analysis of a proximal Gauss-Newton method. - Saverio Salzo; Silvia Villa (Comput. Optim. Appl., 2012)

Dictionary learning improves subtyping of breast cancer aCGH data. - Salvatore Masecchia; Annalisa Barla; Saverio Salzo; Alessandro Verri (EMBC, 2013)

A dictionary learning based method for aCGH segmentation. - Salvatore Masecchia; Saverio Salzo; Annalisa Barla; Alessandro Verri (ESANN, 2013)

Accelerated and Inexact Forward-Backward Algorithms. - Silvia Villa; Saverio Salzo; Luca Baldassarre; Alessandro Verri (SIAM J. Optim., 2013)

Alternating Proximal Regularized Dictionary Learning. - Saverio Salzo; Salvatore Masecchia; Alessandro Verri; Annalisa Barla (Neural Comput., 2014)

The Variable Metric Forward-Backward Splitting Algorithm Under Mild Differentiability Assumptions. - Saverio Salzo (SIAM J. Optim., 2017)

Solving lp-norm regularization with tensor kernels. - Saverio Salzo; Lorenzo Rosasco; Johan A. K. Suykens (AISTATS, 2018)

Bilevel Programming for Hyperparameter Optimization and Meta-Learning. - Luca Franceschi 001; Paolo Frasconi; Saverio Salzo; Riccardo Grazzi; Massimiliano Pontil (ICML, 2018)

Latent Variable Time-varying Network Inference. - Federico Tomasi; Veronica Tozzo; Saverio Salzo; Alessandro Verri (KDD, 2018)

Bilevel learning of the Group Lasso structure. - Jordan Frécon; Saverio Salzo; Massimiliano Pontil (NeurIPS, 2018)

Forward-Backward Splitting for Time-Varying Graphical Models. - Federico Tomasi; Veronica Tozzo; Alessandro Verri; Saverio Salzo (PGM, 2018)

Bilevel Programming for Hyperparameter Optimization and Meta-Learning. - Luca Franceschi 001; Paolo Frasconi; Saverio Salzo; Massimiliano Pontil (CoRR, 2018)

Far-HO: A Bilevel Programming Package for Hyperparameter Optimization and Meta-Learning. - Luca Franceschi 001; Riccardo Grazzi; Massimiliano Pontil; Saverio Salzo; Paolo Frasconi (CoRR, 2018)

Consistent learning by composite proximal thresholding. - Patrick L. Combettes; Saverio Salzo; Silvia Villa (Math. Program., 2018)

Sinkhorn Barycenters with Free Support via Frank-Wolfe Algorithm. - Giulia Luise; Saverio Salzo; Massimiliano Pontil; Carlo Ciliberto (NeurIPS, 2019)

On the Iteration Complexity of Hypergradient Computation. - Riccardo Grazzi; Luca Franceschi 001; Massimiliano Pontil; Saverio Salzo (ICML, 2020)

Unveiling Groups of Related Tasks in Multi - Task Learning. - Jordan Frécon; Saverio Salzo; Massimiliano Pontil (ICPR, 2020)

Efficient Tensor Kernel methods for sparse regression. - Feliks Hibraj; Marcello Pelillo; Saverio Salzo; Massimiliano Pontil (CoRR, 2020)

Convergence Properties of Stochastic Hypergradients. - Riccardo Grazzi; Massimiliano Pontil; Saverio Salzo (AISTATS, 2021)

Convergence of Batch Greenkhorn for Regularized Multimarginal Optimal Transport. - Vladimir Kostic; Saverio Salzo; Massimiliano Pontil (CoRR, 2021)

Bregman Neural Networks. - Jordan Frécon; Gilles Gasso; Massimiliano Pontil; Saverio Salzo (ICML, 2022)

Batch Greenkhorn Algorithm for Entropic-Regularized Multimarginal Optimal Transport: Linear Rate of Convergence and Iteration Complexity. - Vladimir R. Kostic; Saverio Salzo; Massimiliano Pontil (ICML, 2022)

Parallel random block-coordinate forward-backward algorithm: a unified convergence analysis. - Saverio Salzo; Silvia Villa (Math. Program., 2022)

Relax and penalize: a new bilevel approach to mixed-binary hyperparameter optimization. - Marianna De Santis; Jordan Frécon; Francesco Rinaldi; Saverio Salzo; Martin Schmidt 003 (CoRR, 2023)

Bilevel Optimization with a Lower-level Contraction: Optimal Sample Complexity without Warm-Start. - Riccardo Grazzi; Massimiliano Pontil; Saverio Salzo (J. Mach. Learn. Res., 2023)

The method of randomized Bregman projections for stochastic feasibility problems. - Vladimir R. Kostic; Saverio Salzo (Numer. Algorithms, 2023)

Convergence of an asynchronous block-coordinate forward-backward algorithm for convex composite optimization. - Cheik Traoré; Saverio Salzo; Silvia Villa (Comput. Optim. Appl., 2023)

Nonsmooth Implicit Differentiation: Deterministic and Stochastic Convergence Rates. - Riccardo Grazzi; Massimiliano Pontil; Saverio Salzo (ICML, 2024)

High Probability Bounds for Stochastic Subgradient Schemes with Heavy Tailed Noise]. - Daniela Angela Parletta; Andrea Paudice; Massimiliano Pontil; Saverio Salzo (SIAM J. Math. Data Sci., 2024)

Variance Reduction Techniques for Stochastic Proximal Point Algorithms. - Cheik Traoré; Vassilis Apidopoulos; Saverio Salzo; Silvia Villa (J. Optim. Theory Appl., 2024)

Relax and penalize: a new bilevel approach to mixed-binary hyperparameter optimization. - Sara Venturini; Marianna De Santis; Jordan Patracone; Martin Schmidt 003; Francesco Rinaldi; Saverio Salzo (Trans. Mach. Learn. Res., 2025)