Rudi, Alessandro

48 publications

NeurIPS 2025 Dynamic Regret Reduces to Kernelized Static Regret Andrew Jacobsen, Alessandro Rudi, Francesco Orabona, Nicolò Cesa-Bianchi

NeurIPS 2025 Safely Learning Controlled Stochastic Dynamics Luc Brogat-Motte, Alessandro Rudi, Riccardo Bonalli

NeurIPS 2023 Efficient Sampling of Stochastic Differential Equations with Positive Semi-Definite Models Anant Raj, Umut Simsekli, Alessandro Rudi

NeurIPS 2023 GloptiNets: Scalable Non-Convex Optimization with Certificates Gaspard Beugnot, Julien Mairal, Alessandro Rudi

AISTATS 2022 On the Consistency of Max-Margin Losses Alex Nowak, Alessandro Rudi, Francis Bach

AISTATS 2022 Sampling from Arbitrary Functions via PSD Models Ulysse Marteau-Ferey, Francis Bach, Alessandro Rudi

NeurIPS 2022 Active Labeling: Streaming Stochastic Gradients Vivien Cabannes, Francis R. Bach, Vianney Perchet, Alessandro Rudi

ICML 2022 Measuring Dissimilarity with Diffeomorphism Invariance Théophile Cantelobre, Carlo Ciliberto, Benjamin Guedj, Alessandro Rudi

COLT 2022 Non-Convex Optimization with Certificates and Fast Rates Through Kernel Sums of Squares Blake Woodworth, Francis Bach, Alessandro Rudi

ICML 2022 Nyström Kernel Mean Embeddings Antoine Chatalic, Nicolas Schreuder, Lorenzo Rosasco, Alessandro Rudi

COLT 2022 On the Benefits of Large Learning Rates for Kernel Methods Gaspard Beugnot, Julien Mairal, Alessandro Rudi

JMLR 2022 Vector-Valued Least-Squares Regression Under Output Regularity Assumptions Luc Brogat-Motte, Alessandro Rudi, Céline Brouard, Juho Rousu, Florence d'Alché-Buc

COLT 2021 A Dimension-Free Computational Upper-Bound for Smooth Optimal Transport Estimation Adrien Vacher, Boris Muzellec, Alessandro Rudi, Francis Bach, Francois-Xavier Vialard

NeurIPS 2021 Beyond Tikhonov: Faster Learning with Self-Concordant Losses, via Iterative Regularization Gaspard Beugnot, Julien Mairal, Alessandro Rudi

ICML 2021 Disambiguation of Weak Supervision Leading to Exponential Convergence Rates Vivien A Cabannnes, Francis Bach, Alessandro Rudi

COLT 2021 Fast Rates for Structured Prediction Vivien A Cabannes, Francis Bach, Alessandro Rudi

NeurIPS 2021 Mixability Made Efficient: Fast Online Multiclass Logistic Regression Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi

NeurIPS 2021 Overcoming the Curse of Dimensionality with Laplacian Regularization in Semi-Supervised Learning Vivien Cabannes, Loucas Pillaud-Vivien, Francis R. Bach, Alessandro Rudi

NeurIPS 2021 PSD Representations for Effective Probability Models Alessandro Rudi, Carlo Ciliberto

JMLR 2020 A General Framework for Consistent Structured Prediction with Implicit Loss Embeddings Carlo Ciliberto, Lorenzo Rosasco, Alessandro Rudi

ICML 2020 Consistent Structured Prediction with Max-Min Margin Markov Networks Alex Nowak, Francis Bach, Alessandro Rudi

COLT 2020 Efficient Improper Learning for Online Logistic Regression Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi

AISTATS 2020 Gain with No Pain: Efficiency of Kernel-PCA by Nyström Sampling Nicholas Sterge, Bharath Sriperumbudur, Lorenzo Rosasco, Alessandro Rudi

NeurIPS 2020 Kernel Methods Through the Roof: Handling Billions of Points Efficiently Giacomo Meanti, Luigi Carratino, Lorenzo Rosasco, Alessandro Rudi

NeurIPS 2020 Non-Parametric Models for Non-Negative Functions Ulysse Marteau-Ferey, Francis R. Bach, Alessandro Rudi

AISTATS 2020 Statistical Estimation of the Poincaré Constant and Application to Sampling Multimodal Distributions Loucas Pillaud-Vivien, Francis Bach, Tony Lelièvre, Alessandro Rudi, Gabriel Stoltz

ICML 2020 Structured Prediction with Partial Labelling Through the Infimum Loss Vivien Cabannnes, Alessandro Rudi, Francis Bach

COLT 2019 Affine Invariant Covariance Estimation for Heavy-Tailed Distributions Dmitrii M. Ostrovskii, Alessandro Rudi

COLT 2019 Beyond Least-Squares: Fast Rates for Regularized Empirical Risk Minimization Through Self-Concordance Ulysse Marteau-Ferey, Dmitrii Ostrovskii, Francis Bach, Alessandro Rudi

NeurIPS 2019 Efficient Online Learning with Kernels for Adversarial Large Scale Problems Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi

NeurIPS 2019 Globally Convergent Newton Methods for Ill-Conditioned Generalized Self-Concordant Losses Ulysse Marteau-Ferey, Francis Bach, Alessandro Rudi

NeurIPS 2019 Localized Structured Prediction Carlo Ciliberto, Francis Bach, Alessandro Rudi

NeurIPS 2019 Massively Scalable Sinkhorn Distances via the Nyström Method Jason Altschuler, Francis Bach, Alessandro Rudi, Jonathan Niles-Weed

AISTATS 2019 Sharp Analysis of Learning with Discrete Losses Alex Nowak, Francis Bach, Alessandro Rudi

NeurIPS 2018 Differential Properties of Sinkhorn Approximation for Learning with Wasserstein Distance Giulia Luise, Alessandro Rudi, Massimiliano Pontil, Carlo Ciliberto

COLT 2018 Exponential Convergence of Testing Error for Stochastic Gradient Methods Loucas Pillaud-Vivien, Alessandro Rudi, Francis R. Bach

NeurIPS 2018 Learning with SGD and Random Features Luigi Carratino, Alessandro Rudi, Lorenzo Rosasco

NeurIPS 2018 Manifold Structured Prediction Alessandro Rudi, Carlo Ciliberto, GianMaria Marconi, Lorenzo Rosasco

NeurIPS 2018 On Fast Leverage Score Sampling and Optimal Learning Alessandro Rudi, Daniele Calandriello, Luigi Carratino, Lorenzo Rosasco

NeurIPS 2018 Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems Through Multiple Passes Loucas Pillaud-Vivien, Alessandro Rudi, Francis Bach

NeurIPS 2017 Consistent Multitask Learning with Nonlinear Output Relations Carlo Ciliberto, Alessandro Rudi, Lorenzo Rosasco, Massimiliano Pontil

NeurIPS 2017 FALKON: An Optimal Large Scale Kernel Method Alessandro Rudi, Luigi Carratino, Lorenzo Rosasco

NeurIPS 2017 Generalization Properties of Learning with Random Features Alessandro Rudi, Lorenzo Rosasco

NeurIPS 2016 A Consistent Regularization Approach for Structured Prediction Carlo Ciliberto, Lorenzo Rosasco, Alessandro Rudi

AISTATS 2016 NYTRO: When Subsampling Meets Early Stopping Raffaello Camoriano, Tomás Angles, Alessandro Rudi, Lorenzo Rosasco

NeurIPS 2015 Less Is More: Nyström Computational Regularization Alessandro Rudi, Raffaello Camoriano, Lorenzo Rosasco

NeurIPS 2013 On the Sample Complexity of Subspace Learning Alessandro Rudi, Guillermo D Canas, Lorenzo Rosasco

CVPR 2011 A General Method for the Point of Regard Estimation in 3D Space Fiora Pirri, Matia Pizzoli, Alessandro Rudi