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20172026
most citedOn the Iteration Complexity of Hypergradient Computation

23 citations · 33 across the 6 of their papers we have counts for

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6 papers · 1 filter

stat.ML2026

AdaGrad-Diff: A New Version of the Adaptive Gradient Algorithm

Matia Bojovic, Saverio Salzo, Massimiliano Pontil

Vanilla gradient methods are often highly sensitive to the choice of stepsize, which typically requires manual tuning. Adaptive methods alleviate this issue and have therefore beco…

stat.ML202023 cited

On the Iteration Complexity of Hypergradient Computation

Riccardo Grazzi, Luca Franceschi, Massimiliano Pontil +1

We study a general class of bilevel problems, consisting in the minimization of an upper-level objective which depends on the solution to a parametric fixed-point equation. Importa…

stat.ML20199 cited

Sinkhorn Barycenters with Free Support via Frank-Wolfe Algorithm

Giulia Luise, Saverio Salzo, Massimiliano Pontil +1

We present a novel algorithm to estimate the barycenter of arbitrary probability distributions with respect to the Sinkhorn divergence. Based on a Frank-Wolfe optimization strategy…

stat.ML2018

Bilevel Programming for Hyperparameter Optimization and Meta-Learning

Luca Franceschi, Paolo Frasconi, Saverio Salzo +2

We introduce a framework based on bilevel programming that unifies gradient-based hyperparameter optimization and meta-learning. We show that an approximate version of the bilevel…

stat.ML2018

Latent Variable Time-varying Network Inference

Federico Tomasi, Veronica Tozzo, Saverio Salzo +1

In many applications of finance, biology and sociology, complex systems involve entities interacting with each other. These processes have the peculiarity of evolving over time and…

stat.ML2017

Solving -norm regularization with tensor kernels

Saverio Salzo, Johan A. K. Suykens, Lorenzo Rosasco

In this paper, we discuss how a suitable family of tensor kernels can be used to efficiently solve nonparametric extensions of regularized learning methods. Our main contr…