639 citations · 2.9k across the 94 of their papers we have counts for
7 papers · 2 filters
Online Model Selection: a Rested Bandit Formulation
Leonardo Cella, Claudio Gentile, Massimiliano Pontil
Motivated by a natural problem in online model selection with bandit information, we introduce and analyze a best arm identification problem in the rested bandit setting, wherein a…
Convergence Properties of Stochastic Hypergradients
Riccardo Grazzi, Massimiliano Pontil, Saverio Salzo
Bilevel optimization problems are receiving increasing attention in machine learning as they provide a natural framework for hyperparameter optimization and meta-learning. A key st…
Generalization Properties of Optimal Transport GANs with Latent Distribution Learning
Giulia Luise, Massimiliano Pontil, Carlo Ciliberto
The Generative Adversarial Networks (GAN) framework is a well-established paradigm for probability matching and realistic sample generation. While recent attention has been devoted…
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…
Fair Regression with Wasserstein Barycenters
Evgenii Chzhen, Christophe Denis, Mohamed Hebiri +2
We study the problem of learning a real-valued function that satisfies the Demographic Parity constraint. It demands the distribution of the predicted output to be independent of t…
Meta-learning with Stochastic Linear Bandits
Leonardo Cella, Alessandro Lazaric, Massimiliano Pontil
We investigate meta-learning procedures in the setting of stochastic linear bandits tasks. The goal is to select a learning algorithm which works well on average over a class of ba…