Riccardo Grazzi

According to our database, Riccardo Grazzi authored at least 12 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Is Mamba Capable of In-Context Learning?

Riccardo Grazzi, Julien Siems, Simon Schrodi, Thomas Brox, Frank Hutter

CoRR, 2024

Nonsmooth Implicit Differentiation: Deterministic and Stochastic Convergence Rates.

Riccardo Grazzi, Massimiliano Pontil, Saverio Salzo

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Learning invariant representations of time-homogeneous stochastic dynamical systems.

Vladimir R. Kostic, Pietro Novelli, Riccardo Grazzi, Karim Lounici, Massimiliano Pontil

Proceedings of the Twelfth International Conference on Learning Representations, 2024

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

Deep projection networks for learning time-homogeneous dynamical systems.

Vladimir R. Kostic, Pietro Novelli, Riccardo Grazzi, Karim Lounici, Massimiliano Pontil

CoRR, 2023

2022

Group Meritocratic Fairness in Linear Contextual Bandits.

Riccardo Grazzi, Arya Akhavan, John Isak Texas Falk, Leonardo Cella, Massimiliano Pontil

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Meta-Forecasting by combining Global Deep Representations with Local Adaptation.

Riccardo Grazzi, Valentin Flunkert, David Salinas, Tim Januschowski, Matthias W. Seeger, Cédric Archambeau

CoRR, 2021

Convergence Properties of Stochastic Hypergradients.

Riccardo Grazzi, Massimiliano Pontil, Saverio Salzo

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

On the Iteration Complexity of Hypergradient Computation.

Riccardo Grazzi, Luca Franceschi, Massimiliano Pontil, Saverio Salzo

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Learning-to-Learn Stochastic Gradient Descent with Biased Regularization.

Giulia Denevi, Carlo Ciliberto, Riccardo Grazzi, Massimiliano Pontil

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Far-HO: A Bilevel Programming Package for Hyperparameter Optimization and Meta-Learning.

Luca Franceschi, Riccardo Grazzi, Massimiliano Pontil, Saverio Salzo, Paolo Frasconi

CoRR, 2018

Bilevel Programming for Hyperparameter Optimization and Meta-Learning.

Luca Franceschi, Paolo Frasconi, Saverio Salzo, Riccardo Grazzi, Massimiliano Pontil

Proceedings of the 35th International Conference on Machine Learning, 2018