Luigi Carratino | DeepAI

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∙ 01/30/2022

Scaling Gaussian Process Optimization by Evaluating a Few Unique Candidates Multiple Times

Computing a Gaussian process (GP) posterior has a computational cost cub...

0 Daniele Calandriello, et al. ∙

∙ 01/17/2022

Efficient Hyperparameter Tuning for Large Scale Kernel Ridge Regression

Kernel methods provide a principled approach to nonparametric learning. ...

0 Giacomo Meanti, et al. ∙

∙ 10/21/2021

Mean Nyström Embeddings for Adaptive Compressive Learning

Compressive learning is an approach to efficient large scale learning ba...

0 Antoine Chatalic, et al. ∙

∙ 06/23/2021

ParK: Sound and Efficient Kernel Ridge Regression by Feature Space Partitions

We introduce ParK, a new large-scale solver for kernel ridge regression....

0 Luigi Carratino, et al. ∙

∙ 06/16/2021

Ada-BKB: Scalable Gaussian Process Optimization on Continuous Domain by Adaptive Discretization

Gaussian process optimization is a successful class of algorithms (e.g. ...

0 Marco Rando, et al. ∙

∙ 06/18/2020

Kernel methods through the roof: handling billions of points efficiently

Kernel methods provide an elegant and principled approach to nonparametr...

0 Giacomo Meanti, et al. ∙

∙ 06/10/2020

On Mixup Regularization

Mixup is a data augmentation technique that creates new examples as conv...

0 Luigi Carratino, et al. ∙

∙ 02/23/2020

Near-linear Time Gaussian Process Optimization with Adaptive Batching and Resparsification

Gaussian processes (GP) are one of the most successful frameworks to mod...

2 Daniele Calandriello, et al. ∙

∙ 03/13/2019

Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret

Gaussian processes (GP) are a popular Bayesian approach for the optimiza...

4 Daniele Calandriello, et al. ∙

∙ 10/31/2018

On Fast Leverage Score Sampling and Optimal Learning

Leverage score sampling provides an appealing way to perform approximate...

24 Alessandro Rudi, et al. ∙

∙ 07/17/2018

Learning with SGD and Random Features

Sketching and stochastic gradient methods are arguably the most common t...

2 Luigi Carratino, et al. ∙

∙ 05/31/2017

FALKON: An Optimal Large Scale Kernel Method

Kernel methods provide a principled way to perform non linear, nonparame...

0 Alessandro Rudi, et al. ∙

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