Pubblicazioni di Salzo Saverio
2024
Angela Parletta Daniela, Paudice Andrea, Pontil Massimiliano, Salzo Saverio
High Probability Bounds for Stochastic Subgradient Schemes with Heavy Tailed Noise. SIAM JOURNAL ON MATHEMATICS OF DATA SCIENCE 2024: 953-977
Grazzi R., Pontil M., Salzo S.
Nonsmooth Implicit Differentiation: Deterministic and Stochastic Convergence Rates. Proceedings of the 41st International Conference on Machine Learning 2024: 16250-16274
Traore Cheik, Apidopoulos Vassilis, Salzo Saverio, Villa Silvia
Variance Reduction Techniques for Stochastic Proximal Point Algorithms. JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 2024: -
2023
Grazzi Riccardo, Pontil Massimiliano, Salzo Saverio
Bilevel Optimization with a Lower-level Contraction: Optimal Sample Complexity without Warm-Start. JOURNAL OF MACHINE LEARNING RESEARCH 2023: 1-37
Traoré Cheik, Salzo Saverio, Villa Silvia
Convergence of an asynchronous block-coordinate forward-backward algorithm for convex composite optimization. COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2023: -
2022
Kostic ́ Vladimir R., Salzo Saverio, Pontil Massimiliano
Batch Greenkhorn Algorithm for Entropic-Regularized Multimarginal Optimal Transport: Linear Rate of Convergence and Iteration Complexity. Proceedings of the 39th International Conference on Machine Learning 2022: -
Frecon Jordan, Gasso Gilles, Pontil Massimiliano, Salzo Saverio
Bregman Neural Networks. Proceedings of the 39th International Conference on Machine Learning 2022: -
Salzo S, Villa S
Parallel random block-coordinate forward-backward algorithm: a unified convergence analysis. MATHEMATICAL PROGRAMMING 2022: 225-269
Kostic Vr, Salzo S
The method of randomized Bregman projections for stochastic feasibility problems. NUMERICAL ALGORITHMS 2022: -
2021
Grazzi R, Pontil M, Salzo S
Convergence Properties of Stochastic Hypergradients. 2021: 3826-3834
Salzo S., Villa S.
Parallel random block-coordinate forward–backward algorithm: a unified convergence analysis. MATHEMATICAL PROGRAMMING 2021: 1-45
Salzo Saverio, Villa Silvia
Proximal Gradient Methods for Machine Learning and Imaging. Harmonic and Applied Analysis. From Radon Transforms to Machine Learning. 2021: 149-244
Frecon J, Salzo S, Pontil M
2020
Salzo S, Suykens Jak
Generalized support vector regression: Duality and tensor-kernel representation. ANALYSIS AND APPLICATIONS 2020: 149-183
Grazzi R, Franceschi L, Pontil M, Salzo S
On the Iteration Complexity of Hypergradient Computation. 2020: 3748-3758
2019
Luise G, Salzo S, Pontil M, Ciliberto C
2018
Frecon J, Salzo S, Pontil M
Franceschi L, Frasconi P, Salzo S, Grazzi R, Pontil M
Combettes Patrick L., Salzo Saverio, Villa Silvia
Consistent learning by composite proximal thresholding. MATHEMATICAL PROGRAMMING 2018: 99-127
Tomasi F, Tozzo V, Verri A, Salzo S
Forward-Backward Splitting for Time-Varying Graphical Models. International Conference on Probabilistic Graphical Models 2018: 475-486
Tomasi Federico, Salzo Saverio, Tozzo Veronica, Verri Alessandro
Latent variable time-varying network inference. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 2018: 2338-2346
Combettes Pl, Salzo S, Villa S
Regularized learning schemes in feature Banach spaces. ANALYSIS AND APPLICATIONS 2018: 1-54
Salzo S, Suykens Jak, Rosasco L
Solving l(p)-norm regularization with tensor kernels. International Conference on Artificial Intelligence and Statistics (AISTATS) 2018: -