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ORCIDRiccardo Grazzi
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2020 – today
- 2024
[c7]Vladimir R. Kostic, Pietro Novelli, Riccardo Grazzi, Karim Lounici, Massimiliano Pontil:
Learning invariant representations of time-homogeneous stochastic dynamical systems. ICLR 2024- [c6]Riccardo Grazzi, Massimiliano Pontil, Saverio Salzo:
Nonsmooth Implicit Differentiation: Deterministic and Stochastic Convergence Rates. ICML 2024 - [i10]Riccardo Grazzi, Julien Siems, Simon Schrodi, Thomas Brox, Frank Hutter:
Is Mamba Capable of In-Context Learning? CoRR abs/2402.03170 (2024) - [i9]Riccardo Grazzi, Massimiliano Pontil, Saverio Salzo:
Nonsmooth Implicit Differentiation: Deterministic and Stochastic Convergence Rates. CoRR abs/2403.11687 (2024) - 2023
- [j1]Riccardo Grazzi, Massimiliano Pontil, Saverio Salzo:
Bilevel Optimization with a Lower-level Contraction: Optimal Sample Complexity without Warm-Start. J. Mach. Learn. Res. 24: 167:1-167:37 (2023) - [i8]Vladimir R. Kostic, Pietro Novelli, Riccardo Grazzi, Karim Lounici, Massimiliano Pontil:
Deep projection networks for learning time-homogeneous dynamical systems. CoRR abs/2307.09912 (2023) - 2022
- [c5]Riccardo Grazzi, Arya Akhavan, John Isak Texas Falk, Leonardo Cella, Massimiliano Pontil:
Group Meritocratic Fairness in Linear Contextual Bandits. NeurIPS 2022 - [i7]Riccardo Grazzi, Massimiliano Pontil, Saverio Salzo:
Bilevel Optimization with a Lower-level Contraction: Optimal Sample Complexity without Warm-Start. CoRR abs/2202.03397 (2022) - [i6]Riccardo Grazzi, Arya Akhavan, John Isak Texas Falk
, Leonardo Cella, Massimiliano Pontil:
Group Meritocratic Fairness in Linear Contextual Bandits. CoRR abs/2206.03150 (2022) - 2021
- [c4]Riccardo Grazzi, Massimiliano Pontil, Saverio Salzo:
Convergence Properties of Stochastic Hypergradients. AISTATS 2021: 3826-3834 - [i5]Riccardo Grazzi, Valentin Flunkert, David Salinas, Tim Januschowski, Matthias W. Seeger, Cédric Archambeau:
Meta-Forecasting by combining Global Deep Representations with Local Adaptation. CoRR abs/2111.03418 (2021) - 2020
- [c3]Riccardo Grazzi, Luca Franceschi, Massimiliano Pontil, Saverio Salzo:
On the Iteration Complexity of Hypergradient Computation. ICML 2020: 3748-3758 - [i4]Riccardo Grazzi, Luca Franceschi, Massimiliano Pontil, Saverio Salzo:
On the Iteration Complexity of Hypergradient Computation. CoRR abs/2006.16218 (2020) - [i3]Riccardo Grazzi, Massimiliano Pontil, Saverio Salzo:
Convergence Properties of Stochastic Hypergradients. CoRR abs/2011.07122 (2020)
2010 – 2019
- 2019
- [c2]Giulia Denevi, Carlo Ciliberto, Riccardo Grazzi, Massimiliano Pontil:
Learning-to-Learn Stochastic Gradient Descent with Biased Regularization. ICML 2019: 1566-1575 - [i2]Giulia Denevi, Carlo Ciliberto, Riccardo Grazzi, Massimiliano Pontil:
Learning-to-Learn Stochastic Gradient Descent with Biased Regularization. CoRR abs/1903.10399 (2019) - 2018
- [c1]Luca Franceschi, Paolo Frasconi, Saverio Salzo, Riccardo Grazzi, Massimiliano Pontil:
Bilevel Programming for Hyperparameter Optimization and Meta-Learning. ICML 2018: 1563-1572 - [i1]Luca Franceschi, Riccardo Grazzi, Massimiliano Pontil, Saverio Salzo, Paolo Frasconi:
Far-HO: A Bilevel Programming Package for Hyperparameter Optimization and Meta-Learning. CoRR abs/1806.04941 (2018)
Coauthor Index
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last updated on 2024-09-13 01:39 CEST by the dblp team
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