Alessandro Rudi
Alessandro Rudi
INRIA - École Normale Supérieure
Verifierad e-postadress på inria.fr - Startsida
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Less is More: Nyström Computational Regularization
A Rudi, R Camoriano, L Rosasco
Advances in Neural Information Processing Systems (NIPS) 2015, 2015
2212015
Generalization Properties of Learning with Random Features
A Rudi, L Rosasco
Advances in Neural Information Processing Systems, 2017
1982017
Falkon: An optimal large scale kernel method
A Rudi, L Carratino, L Rosasco
arXiv preprint arXiv:1705.10958, 2017
1142017
Differential Properties of Sinkhorn Approximation for Learning with Wasserstein Distance
G Luise, A Rudi, M Pontil, C Ciliberto
Advances in Neural Information Processing Systems, 2018
692018
A general method for the point of regard estimation in 3D space
F Pirri, M Pizzoli, A Rudi
CVPR 2011, 921-928, 2011
592011
Massively scalable sinkhorn distances via the nystr\" om method
J Altschuler, F Bach, A Rudi, J Niles-Weed
arXiv preprint arXiv:1812.05189, 2018
542018
Learning with SGD and Random Features
L Carratino, A Rudi, L Rosasco
Advances in Neural Information Processing Systems, 2018
542018
A consistent regularization approach for structured prediction
C Ciliberto, L Rosasco, A Rudi
Advances in neural information processing systems 29, 4412-4420, 2016
502016
On fast leverage score sampling and optimal learning
A Rudi, D Calandriello, L Carratino, L Rosasco
arXiv preprint arXiv:1810.13258, 2018
492018
Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems through Multiple Passes
L Pillaud-Vivien, A Rudi, F Bach
Advances in Neural Information Processing Systems, 2018
492018
Optimal rates for spectral algorithms with least-squares regression over hilbert spaces
J Lin, A Rudi, L Rosasco, V Cevher
Applied and Computational Harmonic Analysis 48 (3), 868-890, 2020
48*2020
NYTRO: When Subsampling Meets Early Stopping
T Angles, R Camoriano, A Rudi, L Rosasco
arXiv preprint arXiv:1510.05684, 2015
33*2015
Consistent multitask learning with nonlinear output relations
C Ciliberto, A Rudi, L Rosasco, M Pontil
arXiv preprint arXiv:1705.08118, 2017
302017
Beyond least-squares: Fast rates for regularized empirical risk minimization through self-concordance
U Marteau-Ferey, D Ostrovskii, F Bach, A Rudi
Conference on Learning Theory, 2294-2340, 2019
282019
Approximating the quadratic transportation metric in near-linear time
J Altschuler, F Bach, A Rudi, J Weed
arXiv preprint arXiv:1810.10046, 2018
232018
Kernel methods through the roof: handling billions of points efficiently
G Meanti, L Carratino, L Rosasco, A Rudi
arXiv preprint arXiv:2006.10350, 2020
222020
Exponential convergence of testing error for stochastic gradient methods
L Pillaud-Vivien, A Rudi, F Bach
Conference on Learning Theory (COLT), 2018, 2018
212018
On the sample complexity of subspace learning
A Rudi, GD Canas, L Rosasco
arXiv preprint arXiv:1408.5032, 2014
212014
Globally convergent newton methods for ill-conditioned generalized self-concordant losses
U Marteau-Ferey, F Bach, A Rudi
arXiv preprint arXiv:1907.01771, 2019
172019
Localized structured prediction
C Ciliberto, F Bach, A Rudi
152019
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Artiklar 1–20