Ernesto De Vito

According to our database, Ernesto De Vito authored at least 37 papers between 2004 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Neural reproducing kernel Banach spaces and representer theorems for deep networks.

Francesca Bartolucci, Ernesto De Vito, Lorenzo Rosasco, Stefano Vigogna

CoRR, 2024

2023

Efficient Numerical Integration in Reproducing Kernel Hilbert Spaces via Leverage Scores Sampling.

Antoine Chatalic, Nicolas Schreuder, Ernesto De Vito, Lorenzo Rosasco

CoRR, 2023

2022

Multiclass learning with margin: exponential rates with no bias-variance trade-off.

Stefano Vigogna, Giacomo Meanti, Ernesto De Vito, Lorenzo Rosasco

Proceedings of the International Conference on Machine Learning, 2022

Efficient Hyperparameter Tuning for Large Scale Kernel Ridge Regression.

Giacomo Meanti, Luigi Carratino, Ernesto De Vito, Lorenzo Rosasco

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Mean Nyström Embeddings for Adaptive Compressive Learning.

Antoine Chatalic, Luigi Carratino, Ernesto De Vito, Lorenzo Rosasco

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Understanding neural networks with reproducing kernel Banach spaces.

Francesca Bartolucci, Ernesto De Vito, Lorenzo Rosasco, Stefano Vigogna

CoRR, 2021

Learning the optimal regularizer for inverse problems.

Giovanni S. Alberti, Ernesto De Vito, Matti Lassas, Luca Ratti, Matteo Santacesaria

CoRR, 2021

Learning the optimal Tikhonov regularizer for inverse problems.

Giovanni S. Alberti, Ernesto De Vito, Matti Lassas, Luca Ratti, Matteo Santacesaria

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Regularized ERM on random subspaces.

Andrea Della Vecchia, Jaouad Mourtada, Ernesto De Vito, Lorenzo Rosasco

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2019

Unitarization and Inversion Formulae for the Radon Transform Between Dual Pairs.

Giovanni S. Alberti, Francesca Bartolucci, Filippo De Mari, Ernesto De Vito

SIAM J. Math. Anal., 2019

Multi-Scale Vector Quantization with Reconstruction Trees.

Enrico Cecini, Ernesto De Vito, Lorenzo Rosasco

CoRR, 2019

Reproducing kernel Hilbert spaces on manifolds: Sobolev and Diffusion spaces.

Ernesto De Vito, Nicole Mücke, Lorenzo Rosasco

CoRR, 2019

2018

Space-Time Signal Analysis and the 3D Shearlet Transform.

Damiano Malafronte, Ernesto De Vito, Francesca Odone

J. Math. Imaging Vis., 2018

A Learning Theory Approach to a Computationally Efficient Parameter Selection for the Elastic Net.

Ernesto De Vito, Zeljko Kereta, Valeria Naumova

CoRR, 2018

2017

Scale Invariant and Noise Robust Interest Points With Shearlets.

Miguel A. Duval-Poo, Nicoletta Noceti, Francesca Odone, Ernesto De Vito

IEEE Trans. Image Process., 2017

Regularized Kernel Algorithms for Support Estimation.

Alessandro Rudi, Ernesto De Vito, Alessandro Verri, Francesca Odone

Frontiers Appl. Math. Stat., 2017

Detecting Spatio-Temporally Interest Points Using the Shearlet Transform.

Damiano Malafronte, Francesca Odone, Ernesto De Vito

Proceedings of the Pattern Recognition and Image Analysis - 8th Iberian Conference, 2017

2016

Scale Invariant Interest Points with Shearlets.

Miguel A. Duval-Poo, Nicoletta Noceti, Francesca Odone, Ernesto De Vito

CoRR, 2016

Retinal Image Analysis with Shearlets.

Francesco Levet, Miguel A. Duval-Poo, Ernesto De Vito, Francesca Odone

Proceedings of the Italian Chapter Conference 2016, 2016

2015

Edges and Corners With Shearlets.

Miguel A. Duval-Poo, Francesca Odone, Ernesto De Vito

IEEE Trans. Image Process., 2015

Enhancing Signal Discontinuities with Shearlets: An Application to Corner Detection.

Miguel A. Duval-Poo, Francesca Odone, Ernesto De Vito

Proceedings of the Image Analysis and Processing - ICIAP 2015, 2015

The Use of Representations in Applied Harmonic Analysis.

Filippo De Mari, Ernesto De Vito

Proceedings of the Harmonic and Applied Analysis - From Groups to Signals, 2015

2014

Geometrical and computational aspects of Spectral Support Estimation for novelty detection.

Alessandro Rudi, Francesca Odone, Ernesto De Vito

Pattern Recognit. Lett., 2014

2011

A consistent algorithm to solve Lasso, elastic-net and Tikhonov regularization.

Ernesto De Vito, Veronica Umanità, Silvia Villa

J. Complex., 2011

2010

On Learning with Integral Operators.

Lorenzo Rosasco, Mikhail Belkin, Ernesto De Vito

J. Mach. Learn. Res., 2010

Adaptive Kernel Methods Using the Balancing Principle.

Ernesto De Vito, Sergei V. Pereverzyev, Lorenzo Rosasco

Found. Comput. Math., 2010

Spectral Regularization for Support Estimation.

Ernesto De Vito, Lorenzo Rosasco, Alessandro Toigo

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

2009

Elastic-net regularization in learning theory.

Christine De Mol, Ernesto De Vito, Lorenzo Rosasco

J. Complex., 2009

Entropy conditions for <i>L</i> _<i>r</i>-convergence of empirical processes.

Andrea Caponnetto, Ernesto De Vito, Massimiliano Pontil

Adv. Comput. Math., 2009

A Note on Learning with Integral Operators.

Lorenzo Rosasco, Mikhail Belkin, Ernesto De Vito

Proceedings of the COLT 2009, 2009

2008

Spectral Algorithms for Supervised Learning.

L. Lo Gerfo, Lorenzo Rosasco, Francesca Odone, Ernesto De Vito, Alessandro Verri

Neural Comput., 2008

2007

Optimal Rates for the Regularized Least-Squares Algorithm.

Andrea Caponnetto, Ernesto De Vito

Found. Comput. Math., 2007

2005

Learning from Examples as an Inverse Problem.

Ernesto De Vito, Lorenzo Rosasco, Andrea Caponnetto, Umberto De Giovannini, Francesca Odone

J. Mach. Learn. Res., 2005

Model Selection for Regularized Least-Squares Algorithm in Learning Theory.

Ernesto De Vito, Andrea Caponnetto, Lorenzo Rosasco

Found. Comput. Math., 2005

2004

Are Loss Functions All the Same?.

Lorenzo Rosasco, Ernesto De Vito, Andrea Caponnetto, Michele Piana, Alessandro Verri

Neural Comput., 2004

Some Properties of Regularized Kernel Methods

Ernesto De Vito, Lorenzo Rosasco, Andrea Caponnetto, Michele Piana, Alessandro Verri

J. Mach. Learn. Res., 2004

Learning, Regularization and Ill-Posed Inverse Problems.

Lorenzo Rosasco, Andrea Caponnetto, Ernesto De Vito, Francesca Odone, Umberto De Giovannini

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004