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Alessandro Rudi
Alessandro Rudi
INRIA - ╔cole Normale SupÚrieure
Verified email at inria.fr - Homepage
Title
Cited by
Cited by
Year
Less is More: Nystr÷m Computational Regularization
A Rudi, R Camoriano, L Rosasco
Advances in Neural Information Processing Systems (NIPS) 2015, 2015
2582015
Generalization Properties of Learning with Random Features
A Rudi, L Rosasco
Advances in Neural Information Processing Systems, 2017
2462017
Falkon: An optimal large scale kernel method
A Rudi, L Carratino, L Rosasco
Advances in neural information processing systems 30, 2017
1432017
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
922018
Massively scalable Sinkhorn distances via the Nystr÷m method
J Altschuler, F Bach, A Rudi, J Niles-Weed
Advances in neural information processing systems 32, 2019
732019
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
712018
On fast leverage score sampling and optimal learning
A Rudi, D Calandriello, L Carratino, L Rosasco
Advances in Neural Information Processing Systems 31, 2018
652018
Learning with SGD and Random Features
L Carratino, A Rudi, L Rosasco
Advances in Neural Information Processing Systems, 2018
632018
A general method for the point of regard estimation in 3D space
F Pirri, M Pizzoli, A Rudi
CVPR 2011, 921-928, 2011
632011
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
622020
A consistent regularization approach for structured prediction
C Ciliberto, L Rosasco, A Rudi
Advances in neural information processing systems 29, 2016
542016
Kernel methods through the roof: handling billions of points efficiently
G Meanti, L Carratino, L Rosasco, A Rudi
Advances in Neural Information Processing Systems 33, 14410-14422, 2020
522020
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
362019
Consistent multitask learning with nonlinear output relations
C Ciliberto, A Rudi, L Rosasco, M Pontil
Advances in Neural Information Processing Systems 30, 2017
312017
NYTRO: When Subsampling Meets Early Stopping
T Angles, R Camoriano, A Rudi, L Rosasco
arXiv preprint arXiv:1510.05684, 2015
31*2015
Structured prediction with partial labelling through the infimum loss
V Cabannnes, A Rudi, F Bach
International Conference on Machine Learning, 1230-1239, 2020
282020
On the sample complexity of subspace learning
A Rudi, GD Canas, L Rosasco
Advances in Neural Information Processing Systems 26, 2013
262013
Globally convergent newton methods for ill-conditioned generalized self-concordant losses
U Marteau-Ferey, F Bach, A Rudi
Advances in Neural Information Processing Systems 32, 2019
252019
A Dimension-free Computational Upper-bound for Smooth Optimal Transport Estimation
A Vacher, B Muzellec, A Rudi, F Bach, FX Vialard
arXiv preprint arXiv:2101.05380, 2021
242021
Exponential convergence of testing error for stochastic gradient methods
L Pillaud-Vivien, A Rudi, F Bach
Conference on Learning Theory (COLT), 2018, 2018
232018
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Articles 1–20