Alessandro Rudi

According to our database, Alessandro Rudi authored at least 77 papers between 2010 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Finding global minima via kernel approximations.

Alessandro Rudi, Ulysse Marteau-Ferey, Francis R. Bach

Math. Program., January, 2025

2024

Second Order Conditions to Decompose Smooth Functions as Sums of Squares.

Ulysse Marteau-Ferey, Francis R. Bach, Alessandro Rudi

SIAM J. Optim., March, 2024

Optimal Estimation of Smooth Transport Maps with Kernel SoS.

Adrien Vacher, Boris Muzellec, Francis R. Bach, François-Xavier Vialard, Alessandro Rudi

SIAM J. Math. Data Sci., 2024

Learning Controlled Stochastic Differential Equations.

Luc Brogat-Motte, Riccardo Bonalli, Alessandro Rudi

CoRR, 2024

Generalization Bounds of Surrogate Policies for Combinatorial Optimization Problems.

Pierre-Cyril Aubin-Frankowski, Yohann De Castro, Axel Parmentier, Alessandro Rudi

CoRR, 2024

Structured Prediction in Online Learning.

Pierre Boudart, Alessandro Rudi, Pierre Gaillard

CoRR, 2024

Closed-form Filtering for Non-linear Systems.

Théophile Cantelobre, Carlo Ciliberto, Benjamin Guedj, Alessandro Rudi

CoRR, 2024

2023

Exponential Convergence of Sum-of-Squares Hierarchies for Trigonometric Polynomials.

Francis R. Bach, Alessandro Rudi

SIAM J. Optim., September, 2023

Non-Parametric Learning of Stochastic Differential Equations with Fast Rates of Convergence.

Riccardo Bonalli, Alessandro Rudi

CoRR, 2023

Approximation of optimization problems with constraints through kernel Sum-Of-Squares.

Pierre-Cyril Aubin-Frankowski, Alessandro Rudi

CoRR, 2023

Efficient Sampling of Stochastic Differential Equations with Positive Semi-Definite Models.

Anant Raj, Umut Simsekli, Alessandro Rudi

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

GloptiNets: Scalable Non-Convex Optimization with Certificates.

Gaspard Beugnot, Julien Mairal, Alessandro Rudi

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Vector-Valued Least-Squares Regression under Output Regularity Assumptions.

Luc Brogat-Motte, Alessandro Rudi, Céline Brouard, Juho Rousu, Florence d'Alché-Buc

J. Mach. Learn. Res., 2022

Active Labeling: Streaming Stochastic Gradients.

Vivien Cabannes, Francis R. Bach, Vianney Perchet, Alessandro Rudi

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Nyström Kernel Mean Embeddings.

Antoine Chatalic, Nicolas Schreuder, Lorenzo Rosasco, Alessandro Rudi

Proceedings of the International Conference on Machine Learning, 2022

Measuring dissimilarity with diffeomorphism invariance.

Théophile Cantelobre, Carlo Ciliberto, Benjamin Guedj, Alessandro Rudi

Proceedings of the International Conference on Machine Learning, 2022

Non-Convex Optimization with Certificates and Fast Rates Through Kernel Sums of Squares.

Blake E. Woodworth, Francis R. Bach, Alessandro Rudi

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

On the Benefits of Large Learning Rates for Kernel Methods.

Gaspard Beugnot, Julien Mairal, Alessandro Rudi

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Infinite-Dimensional Sums-of-Squares for Optimal Control.

Eloïse Berthier, Justin Carpentier, Alessandro Rudi, Francis R. Bach

Proceedings of the 61st IEEE Conference on Decision and Control, 2022

On the Consistency of Max-Margin Losses.

Alex Nowak, Alessandro Rudi, Francis R. Bach

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

Sampling from Arbitrary Functions via PSD Models.

Ulysse Marteau-Ferey, Francis R. Bach, Alessandro Rudi

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

2021

Near-optimal estimation of smooth transport maps with kernel sums-of-squares.

Boris Muzellec, Adrien Vacher, Francis R. Bach, François-Xavier Vialard, Alessandro Rudi

CoRR, 2021

Learning PSD-valued functions using kernel sums-of-squares.

Boris Muzellec, Francis R. Bach, Alessandro Rudi

CoRR, 2021

A Note on Optimizing Distributions using Kernel Mean Embeddings.

Boris Muzellec, Francis R. Bach, Alessandro Rudi

CoRR, 2021

Max-Margin is Dead, Long Live Max-Margin!

Alex Nowak-Vila, Alessandro Rudi, Francis R. Bach

CoRR, 2021

Online nonparametric regression with Sobolev kernels.

Oleksandr Zadorozhnyi, Pierre Gaillard, Sébastien Gerchinovitz, Alessandro Rudi

CoRR, 2021

Disambiguation of weak supervision with exponential convergence rates.

Vivien Cabannes, Francis R. Bach, Alessandro Rudi

CoRR, 2021

PSD Representations for Effective Probability Models.

Alessandro Rudi, Carlo Ciliberto

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

Mixability made efficient: Fast online multiclass logistic regression.

Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi

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

Overcoming the curse of dimensionality with Laplacian regularization in semi-supervised learning.

Vivien Cabannes, Loucas Pillaud-Vivien, Francis R. Bach, Alessandro Rudi

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

Beyond Tikhonov: faster learning with self-concordant losses, via iterative regularization.

Gaspard Beugnot, Julien Mairal, Alessandro Rudi

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

Disambiguation of Weak Supervision leading to Exponential Convergence rates.

Vivien A. Cabannes, Francis R. Bach, Alessandro Rudi

Proceedings of the 38th International Conference on Machine Learning, 2021

A Dimension-free Computational Upper-bound for Smooth Optimal Transport Estimation.

Adrien Vacher, Boris Muzellec, Alessandro Rudi, Francis R. Bach, François-Xavier Vialard

Proceedings of the Conference on Learning Theory, 2021

Fast Rates for Structured Prediction.

Vivien A. Cabannes, Francis R. Bach, Alessandro Rudi

Proceedings of the Conference on Learning Theory, 2021

2020

Approximating Hamiltonian dynamics with the Nyström method.

Alessandro Rudi, Leonard Wossnig, Carlo Ciliberto, Andrea Rocchetto, Massimiliano Pontil, Simone Severini

Quantum, 2020

A General Framework for Consistent Structured Prediction with Implicit Loss Embeddings.

Carlo Ciliberto, Lorenzo Rosasco, Alessandro Rudi

J. Mach. Learn. Res., 2020

Faster Kriging: Facing High-Dimensional Simulators.

Xuefei Lu, Alessandro Rudi, Emanuele Borgonovo, Lorenzo Rosasco

Oper. Res., 2020

Learning Output Embeddings in Structured Prediction.

Luc Brogat-Motte, Alessandro Rudi, Céline Brouard, Juho Rousu, Florence d'Alché-Buc

CoRR, 2020

Consistent Structured Prediction with Max-Min Margin Markov Networks.

Alex Nowak-Vila, Francis R. Bach, Alessandro Rudi

CoRR, 2020

Structured and Localized Image Restoration.

Thomas Eboli, Alex Nowak-Vila, Jian Sun, Francis R. Bach, Jean Ponce, Alessandro Rudi

CoRR, 2020

Fast quantum learning with statistical guarantees.

Carlo Ciliberto, Andrea Rocchetto, Alessandro Rudi, Leonard Wossnig

CoRR, 2020

Kernel Methods Through the Roof: Handling Billions of Points Efficiently.

Giacomo Meanti, Luigi Carratino, Lorenzo Rosasco, Alessandro Rudi

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Non-parametric Models for Non-negative Functions.

Ulysse Marteau-Ferey, Francis R. Bach, Alessandro Rudi

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Consistent Structured Prediction with Max-Min Margin Markov Networks.

Alex Nowak, Francis R. Bach, Alessandro Rudi

Proceedings of the 37th International Conference on Machine Learning, 2020

Structured Prediction with Partial Labelling through the Infimum Loss.

Vivien Cabannes, Alessandro Rudi, Francis R. Bach

Proceedings of the 37th International Conference on Machine Learning, 2020

Efficient improper learning for online logistic regression.

Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi

Proceedings of the Conference on Learning Theory, 2020

Gain with no Pain: Efficiency of Kernel-PCA by Nyström Sampling.

Nicholas Sterge, Bharath K. Sriperumbudur, Lorenzo Rosasco, Alessandro Rudi

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Statistical Estimation of the Poincaré constant and Application to Sampling Multimodal Distributions.

Loucas Pillaud-Vivien, Francis R. Bach, Tony Lelièvre, Alessandro Rudi, Gabriel Stoltz

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Gain with no Pain: Efficient Kernel-PCA by Nyström Sampling.

Nicholas Sterge, Bharath K. Sriperumbudur, Lorenzo Rosasco, Alessandro Rudi

CoRR, 2019

A General Theory for Structured Prediction with Smooth Convex Surrogates.

Alex Nowak-Vila, Francis R. Bach, Alessandro Rudi

CoRR, 2019

Globally Convergent Newton Methods for Ill-conditioned Generalized Self-concordant Losses.

Ulysse Marteau-Ferey, Francis R. Bach, Alessandro Rudi

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Efficient online learning with kernels for adversarial large scale problems.

Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Localized Structured Prediction.

Carlo Ciliberto, Francis R. Bach, Alessandro Rudi

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Massively scalable Sinkhorn distances via the Nyström method.

Jason M. Altschuler, Francis R. Bach, Alessandro Rudi, Jonathan Niles-Weed

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Affine Invariant Covariance Estimation for Heavy-Tailed Distributions.

Dmitrii M. Ostrovskii, Alessandro Rudi

Proceedings of the Conference on Learning Theory, 2019

Beyond Least-Squares: Fast Rates for Regularized Empirical Risk Minimization through Self-Concordance.

Ulysse Marteau-Ferey, Dmitrii Ostrovskii, Francis R. Bach, Alessandro Rudi

Proceedings of the Conference on Learning Theory, 2019

Sharp Analysis of Learning with Discrete Losses.

Alex Nowak-Vila, Francis R. Bach, Alessandro Rudi

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Approximating the Quadratic Transportation Metric in Near-Linear Time.

Jason M. Altschuler, Francis R. Bach, Alessandro Rudi, Jonathan Weed

CoRR, 2018

Manifold Structured Prediction.

Alessandro Rudi, Carlo Ciliberto, Gian Maria Marconi, Lorenzo Rosasco

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

On Fast Leverage Score Sampling and Optimal Learning.

Alessandro Rudi, Daniele Calandriello, Luigi Carratino, Lorenzo Rosasco

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems through Multiple Passes.

Loucas Pillaud-Vivien, Alessandro Rudi, Francis R. Bach

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Differential Properties of Sinkhorn Approximation for Learning with Wasserstein Distance.

Giulia Luise, Alessandro Rudi, Massimiliano Pontil, Carlo Ciliberto

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Learning with SGD and Random Features.

Luigi Carratino, Alessandro Rudi, Lorenzo Rosasco

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Exponential Convergence of Testing Error for Stochastic Gradient Methods.

Loucas Pillaud-Vivien, Alessandro Rudi, Francis R. Bach

Proceedings of the Conference On Learning Theory, 2018

2017

Regularized Kernel Algorithms for Support Estimation.

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

Frontiers Appl. Math. Stat., 2017

Generalization Properties of Learning with Random Features.

Alessandro Rudi, Lorenzo Rosasco

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

FALKON: An Optimal Large Scale Kernel Method.

Alessandro Rudi, Luigi Carratino, Lorenzo Rosasco

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Consistent Multitask Learning with Nonlinear Output Relations.

Carlo Ciliberto, Alessandro Rudi, Lorenzo Rosasco, Massimiliano Pontil

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

Generalization Properties of Learning with Random Features.

Alessandro Rudi, Raffaello Camoriano, Lorenzo Rosasco

CoRR, 2016

A Consistent Regularization Approach for Structured Prediction.

Carlo Ciliberto, Lorenzo Rosasco, Alessandro Rudi

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

NYTRO: When Subsampling Meets Early Stopping.

Raffaello Camoriano, Tomás Angles, Alessandro Rudi, Lorenzo Rosasco

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

Less is More: Nyström Computational Regularization.

Alessandro Rudi, Raffaello Camoriano, Lorenzo Rosasco

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014

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

Alessandro Rudi, Francesca Odone, Ernesto De Vito

Pattern Recognit. Lett., 2014

2013

On the Sample Complexity of Subspace Learning.

Alessandro Rudi, Guillermo D. Cañas, Lorenzo Rosasco

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

2012

Adaptive Optimization for Cross Validation.

Alessandro Rudi, Gabriele Chiusano, Alessandro Verri

Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

2011

A general method for the point of regard estimation in 3D space.

Fiora Pirri, Matia Pizzoli, Alessandro Rudi

Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

2010

Linear Solvability in the Viewing Graph.

Alessandro Rudi, Matia Pizzoli, Fiora Pirri

Proceedings of the Computer Vision - ACCV 2010, 2010