639 citations · 2.9k across the 94 of their papers we have counts for
13 papers · 1 filter
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…
Robust Unsupervised Learning via L-Statistic Minimization
Andreas Maurer, Daniela A. Parletta, Andrea Paudice +1
Designing learning algorithms that are resistant to perturbations of the underlying data distribution is a problem of wide practical and theoretical importance. We present a genera…
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…
The Advantage of Conditional Meta-Learning for Biased Regularization and Fine-Tuning
Giulia Denevi, Massimiliano Pontil, Carlo Ciliberto
Biased regularization and fine-tuning are two recent meta-learning approaches. They have been shown to be effective to tackle distributions of tasks, in which the tasks' target vec…
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…
Online Parameter-Free Learning of Multiple Low Variance Tasks
Giulia Denevi, Dimitris Stamos, Massimiliano Pontil
We propose a method to learn a common bias vector for a growing sequence of low-variance tasks. Unlike state-of-the-art approaches, our method does not require tuning any hyper-par…