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Ernesto De Vito
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2020 – today
- 2024
- [i12]Francesca Bartolucci, Ernesto De Vito, Lorenzo Rosasco, Stefano Vigogna:
Neural reproducing kernel Banach spaces and representer theorems for deep networks. CoRR abs/2403.08750 (2024) - 2023
- [i11]Antoine Chatalic, Nicolas Schreuder, Ernesto De Vito, Lorenzo Rosasco:
Efficient Numerical Integration in Reproducing Kernel Hilbert Spaces via Leverage Scores Sampling. CoRR abs/2311.13548 (2023) - 2022
- [c11]Giacomo Meanti, Luigi Carratino, Ernesto De Vito, Lorenzo Rosasco:
Efficient Hyperparameter Tuning for Large Scale Kernel Ridge Regression. AISTATS 2022: 6554-6572 - [c10]Antoine Chatalic, Luigi Carratino, Ernesto De Vito, Lorenzo Rosasco:
Mean Nyström Embeddings for Adaptive Compressive Learning. AISTATS 2022: 9869-9889 - [c9]Stefano Vigogna, Giacomo Meanti, Ernesto De Vito, Lorenzo Rosasco:
Multiclass learning with margin: exponential rates with no bias-variance trade-off. ICML 2022: 22260-22269 - [i10]Giacomo Meanti, Luigi Carratino, Ernesto De Vito, Lorenzo Rosasco:
Efficient Hyperparameter Tuning for Large Scale Kernel Ridge Regression. CoRR abs/2201.06314 (2022) - [i9]Stefano Vigogna, Giacomo Meanti, Ernesto De Vito, Lorenzo Rosasco:
Multiclass learning with margin: exponential rates with no bias-variance trade-off. CoRR abs/2202.01773 (2022) - 2021
- [c8]Andrea Della Vecchia, Jaouad Mourtada, Ernesto De Vito, Lorenzo Rosasco:
Regularized ERM on random subspaces. AISTATS 2021: 4006-4014 - [c7]Giovanni S. Alberti, Ernesto De Vito, Matti Lassas, Luca Ratti, Matteo Santacesaria:
Learning the optimal Tikhonov regularizer for inverse problems. NeurIPS 2021: 25205-25216 - [i8]Giovanni S. Alberti, Ernesto De Vito, Matti Lassas, Luca Ratti, Matteo Santacesaria:
Learning the optimal regularizer for inverse problems. CoRR abs/2106.06513 (2021) - [i7]Francesca Bartolucci
, Ernesto De Vito, Lorenzo Rosasco, Stefano Vigogna:
Understanding neural networks with reproducing kernel Banach spaces. CoRR abs/2109.09710 (2021) - [i6]Antoine Chatalic, Luigi Carratino, Ernesto De Vito, Lorenzo Rosasco:
Mean Nyström Embeddings for Adaptive Compressive Learning. CoRR abs/2110.10996 (2021) - 2020
- [i5]Andrea Della Vecchia, Jaouad Mourtada, Ernesto De Vito, Lorenzo Rosasco:
Regularized ERM on random subspaces. CoRR abs/2006.10016 (2020)
2010 – 2019
- 2019
- [j17]Giovanni S. Alberti, Francesca Bartolucci
Unitarization and Inversion Formulae for the Radon Transform Between Dual Pairs. SIAM J. Math. Anal. 51(6): 4356-4381 (2019) - [i4]Ernesto De Vito, Nicole Mücke, Lorenzo Rosasco:
Reproducing kernel Hilbert spaces on manifolds: Sobolev and Diffusion spaces. CoRR abs/1905.10913 (2019) - [i3]Enrico Cecini, Ernesto De Vito, Lorenzo Rosasco:
Multi-Scale Vector Quantization with Reconstruction Trees. CoRR abs/1907.03875 (2019) - 2018
- [j16]Damiano Malafronte
Space-Time Signal Analysis and the 3D Shearlet Transform. J. Math. Imaging Vis. 60(7): 1008-1024 (2018) - [i2]Ernesto De Vito, Zeljko Kereta, Valeria Naumova:
A Learning Theory Approach to a Computationally Efficient Parameter Selection for the Elastic Net. CoRR abs/1809.08696 (2018) - 2017
- [j15]Alessandro Rudi, Ernesto De Vito
Regularized Kernel Algorithms for Support Estimation. Frontiers Appl. Math. Stat. 3: 23 (2017) - [j14]Miguel A. Duval-Poo
Scale Invariant and Noise Robust Interest Points With Shearlets. IEEE Trans. Image Process. 26(6): 2853-2867 (2017) - [c6]Damiano Malafronte, Francesca Odone, Ernesto De Vito
Detecting Spatio-Temporally Interest Points Using the Shearlet Transform. IbPRIA 2017: 501-510 - 2016
- [c5]Francesco Levet, Miguel A. Duval-Poo
Retinal Image Analysis with Shearlets. STAG 2016: 151-156 - [i1]Miguel A. Duval-Poo, Nicoletta Noceti, Francesca Odone, Ernesto De Vito:
Scale Invariant Interest Points with Shearlets. CoRR abs/1607.07639 (2016) - 2015
- [j13]Miguel A. Duval-Poo
Edges and Corners With Shearlets. IEEE Trans. Image Process. 24(11): 3768-3780 (2015) - [c4]Miguel A. Duval-Poo
Enhancing Signal Discontinuities with Shearlets: An Application to Corner Detection. ICIAP (2) 2015: 108-118 - [p1]Filippo De Mari, Ernesto De Vito
The Use of Representations in Applied Harmonic Analysis. Harmonic and Applied Analysis 2015: 7-81 - 2014
- [j12]Alessandro Rudi
Geometrical and computational aspects of Spectral Support Estimation for novelty detection. Pattern Recognit. Lett. 36: 107-116 (2014) - 2011
- [j11]Ernesto De Vito
A consistent algorithm to solve Lasso, elastic-net and Tikhonov regularization. J. Complex. 27(2): 188-200 (2011) - 2010
- [j10]Ernesto De Vito
Adaptive Kernel Methods Using the Balancing Principle. Found. Comput. Math. 10(4): 455-479 (2010) - [j9]Lorenzo Rosasco, Mikhail Belkin, Ernesto De Vito:
On Learning with Integral Operators. J. Mach. Learn. Res. 11: 905-934 (2010) - [c3]Ernesto De Vito, Lorenzo Rosasco, Alessandro Toigo:
Spectral Regularization for Support Estimation. NIPS 2010: 487-495
2000 – 2009
- 2009
- [j8]Andrea Caponnetto
Entropy conditions for L r -convergence of empirical processes. Adv. Comput. Math. 30(4): 355-373 (2009) - [j7]Christine De Mol, Ernesto De Vito
Elastic-net regularization in learning theory. J. Complex. 25(2): 201-230 (2009) - [c2]Lorenzo Rosasco, Mikhail Belkin, Ernesto De Vito:
A Note on Learning with Integral Operators. COLT 2009 - 2008
- [j6]L. Lo Gerfo, Lorenzo Rosasco
Spectral Algorithms for Supervised Learning. Neural Comput. 20(7): 1873-1897 (2008) - 2007
- [j5]Andrea Caponnetto
Optimal Rates for the Regularized Least-Squares Algorithm. Found. Comput. Math. 7(3): 331-368 (2007) - 2005
- [j4]Ernesto De Vito
Model Selection for Regularized Least-Squares Algorithm in Learning Theory. Found. Comput. Math. 5(1): 59-85 (2005) - [j3]Ernesto De Vito, Lorenzo Rosasco, Andrea Caponnetto, Umberto De Giovannini, Francesca Odone:
Learning from Examples as an Inverse Problem. J. Mach. Learn. Res. 6: 883-904 (2005) - 2004
- [j2]Ernesto De Vito, Lorenzo Rosasco, Andrea Caponnetto, Michele Piana, Alessandro Verri:
Some Properties of Regularized Kernel Methods. J. Mach. Learn. Res. 5: 1363-1390 (2004) - [j1]Lorenzo Rosasco
Are Loss Functions All the Same?. Neural Comput. 16(5): 1063-107 (2004) - [c1]Lorenzo Rosasco, Andrea Caponnetto, Ernesto De Vito, Francesca Odone, Umberto De Giovannini:
Learning, Regularization and Ill-Posed Inverse Problems. NIPS 2004: 1145-1152
Coauthor Index
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