32 citations · 116 across the 12 of their papers we have counts for
4 papers · 1 filter
Efficient Hyperparameter Tuning for Large Scale Kernel Ridge Regression
Giacomo Meanti, Luigi Carratino, Ernesto De Vito +1
Kernel methods provide a principled approach to nonparametric learning. While their basic implementations scale poorly to large problems, recent advances showed that approximate so…
Ada-BKB: Scalable Gaussian Process Optimization on Continuous Domains by Adaptive Discretization
Marco Rando, Luigi Carratino, Silvia Villa +1
Gaussian process optimization is a successful class of algorithms(e.g. GP-UCB) to optimize a black-box function through sequential evaluations. However, for functions with continuo…
Kernel methods through the roof: handling billions of points efficiently
Giacomo Meanti, Luigi Carratino, Lorenzo Rosasco +1
Kernel methods provide an elegant and principled approach to nonparametric learning, but so far could hardly be used in large scale problems, since naïve implementations scale poor…
On Mixup Regularization
Luigi Carratino, Moustapha Cissé, Rodolphe Jenatton +1
Mixup is a data augmentation technique that creates new examples as convex combinations of training points and labels. This simple technique has empirically shown to improve the ac…