Alessandro Rudi

118 papers A* 32A 6B 1Journal 71Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Privacy-Preserving LLM Inference in Practice: A Comparative Survey of Techniques, Trade-Offs, and Deployability. IACR Cryptol. ePrint Arch. Davide Andreoletti, Alessandro Rudi, Emanuele Carpanzano, Francesco Lelli, Tiziano Leidi
2025	J	`jnl`	Dynamic Regret Reduces to Kernelized Static Regret. CoRR Andrew Jacobsen, Alessandro Rudi, Francesco Orabona, Nicolò Cesa-Bianchi
2025	J	`jnl`	Enjoying Non-linearity in Multinomial Logistic Bandits. CoRR Pierre Boudart, Pierre Gaillard, Alessandro Rudi
2025	J	`jnl`	Finding global minima via kernel approximations. Math. Program. Alessandro Rudi, Ulysse Marteau-Ferey, Francis R. Bach
2025	J	`jnl`	Safely Learning Controlled Stochastic Dynamics. CoRR Luc Brogat-Motte, Alessandro Rudi, Riccardo Bonalli
2025	J	`jnl`	Solving Moment and Polynomial Optimization Problems on Sobolev Spaces. SIAM J. Optim. Didier Henrion, Alessandro Rudi
2024	J	`jnl`	Closed-form Filtering for Non-linear Systems. CoRR Théophile Cantelobre, Carlo Ciliberto, Benjamin Guedj, Alessandro Rudi
2024	J	`jnl`	Generalization Bounds of Surrogate Policies for Combinatorial Optimization Problems. CoRR Pierre-Cyril Aubin-Frankowski, Yohann de Castro, Axel Parmentier, Alessandro Rudi
2024	J	`jnl`	Learning Controlled Stochastic Differential Equations. CoRR Luc Brogat-Motte, Riccardo Bonalli, Alessandro Rudi
2024	J	`jnl`	Optimal Estimation of Smooth Transport Maps with Kernel SoS. SIAM J. Math. Data Sci. Adrien Vacher, Boris Muzellec, Francis R. Bach, François-Xavier Vialard, Alessandro Rudi
2024	J	`jnl`	Second Order Conditions to Decompose Smooth Functions as Sums of Squares. SIAM J. Optim. Ulysse Marteau-Ferey, Francis R. Bach, Alessandro Rudi
2024	J	`jnl`	Structured Prediction in Online Learning. CoRR Pierre Boudart, Alessandro Rudi, Pierre Gaillard
2023	J	`jnl`	Approximation of optimization problems with constraints through kernel Sum-Of-Squares. CoRR Pierre-Cyril Aubin-Frankowski, Alessandro Rudi
2023	A*	`conf`	Efficient Sampling of Stochastic Differential Equations with Positive Semi-Definite Models. NeurIPS Anant Raj, Umut Simsekli, Alessandro Rudi
2023	J	`jnl`	Efficient Sampling of Stochastic Differential Equations with Positive Semi-Definite Models. CoRR Anant Raj, Umut Simsekli, Alessandro Rudi
2023	J	`jnl`	Exponential Convergence of Sum-of-Squares Hierarchies for Trigonometric Polynomials. SIAM J. Optim. Francis R. Bach, Alessandro Rudi
2023	A*	`conf`	GloptiNets: Scalable Non-Convex Optimization with Certificates. NeurIPS Gaspard Beugnot, Julien Mairal, Alessandro Rudi
2023	J	`jnl`	GloptiNets: Scalable Non-Convex Optimization with Certificates. CoRR Gaspard Beugnot, Julien Mairal, Alessandro Rudi
2023	J	`jnl`	Non-Parametric Learning of Stochastic Differential Equations with Fast Rates of Convergence. CoRR Riccardo Bonalli, Alessandro Rudi
2022	A*	`conf`	Active Labeling: Streaming Stochastic Gradients. NeurIPS Vivien Cabannes, Francis R. Bach, Vianney Perchet, Alessandro Rudi
2022	J	`jnl`	Active Labeling: Streaming Stochastic Gradients. CoRR Vivien Cabannes, Francis R. Bach, Vianney Perchet, Alessandro Rudi
2022	—	`conf`	Infinite-Dimensional Sums-of-Squares for Optimal Control. CDC Eloïse Berthier, Justin Carpentier, Alessandro Rudi, Francis R. Bach
2022	A*	`conf`	Measuring dissimilarity with diffeomorphism invariance. ICML Théophile Cantelobre, Carlo Ciliberto, Benjamin Guedj, Alessandro Rudi
2022	J	`jnl`	Measuring dissimilarity with diffeomorphism invariance. CoRR Théophile Cantelobre, Carlo Ciliberto, Benjamin Guedj, Alessandro Rudi
2022	A*	`conf`	Non-Convex Optimization with Certificates and Fast Rates Through Kernel Sums of Squares. COLT Blake E. Woodworth, Francis R. Bach, Alessandro Rudi
2022	J	`jnl`	Non-Convex Optimization with Certificates and Fast Rates Through Kernel Sums of Squares. CoRR Blake E. Woodworth, Francis R. Bach, Alessandro Rudi
2022	A*	`conf`	Nyström Kernel Mean Embeddings. ICML Antoine Chatalic, Nicolas Schreuder, Lorenzo Rosasco, Alessandro Rudi
2022	J	`jnl`	Nyström Kernel Mean Embeddings. CoRR Antoine Chatalic, Nicolas Schreuder, Alessandro Rudi, Lorenzo Rosasco
2022	A*	`conf`	On the Benefits of Large Learning Rates for Kernel Methods. COLT Gaspard Beugnot, Julien Mairal, Alessandro Rudi
2022	J	`jnl`	On the Benefits of Large Learning Rates for Kernel Methods. CoRR Gaspard Beugnot, Julien Mairal, Alessandro Rudi
2022	A	`conf`	On the Consistency of Max-Margin Losses. AISTATS Alex Nowak, Alessandro Rudi, Francis R. Bach
2022	A	`conf`	Sampling from Arbitrary Functions via PSD Models. AISTATS Ulysse Marteau-Ferey, Francis R. Bach, Alessandro Rudi
2022	J	`jnl`	Vector-Valued Least-Squares Regression under Output Regularity Assumptions. CoRR Luc Brogat-Motte, Alessandro Rudi, Céline Brouard, Juho Rousu, Florence d'Alché-Buc
2022	J	`jnl`	Vector-Valued Least-Squares Regression under Output Regularity Assumptions. J. Mach. Learn. Res. Luc Brogat-Motte, Alessandro Rudi, Céline Brouard, Juho Rousu, Florence d'Alché-Buc
2021	A*	`conf`	A Dimension-free Computational Upper-bound for Smooth Optimal Transport Estimation. COLT Adrien Vacher, Boris Muzellec, Alessandro Rudi, Francis R. Bach, François-Xavier Vialard
2021	J	`jnl`	A Note on Optimizing Distributions using Kernel Mean Embeddings. CoRR Boris Muzellec, Francis R. Bach, Alessandro Rudi
2021	J	`jnl`	Beyond Tikhonov: Faster Learning with Self-Concordant Losses via Iterative Regularization. CoRR Gaspard Beugnot, Julien Mairal, Alessandro Rudi
2021	A*	`conf`	Beyond Tikhonov: faster learning with self-concordant losses, via iterative regularization. NeurIPS Gaspard Beugnot, Julien Mairal, Alessandro Rudi
2021	A*	`conf`	Disambiguation of Weak Supervision leading to Exponential Convergence rates. ICML Vivien A. Cabannes, Francis R. Bach, Alessandro Rudi
2021	J	`jnl`	Disambiguation of weak supervision with exponential convergence rates. CoRR Vivien Cabannes, Francis R. Bach, Alessandro Rudi
2021	A*	`conf`	Fast Rates for Structured Prediction. COLT Vivien A. Cabannes, Francis R. Bach, Alessandro Rudi
2021	J	`jnl`	Fast rates in structured prediction. CoRR Vivien Cabannes, Alessandro Rudi, Francis R. Bach
2021	J	`jnl`	Learning PSD-valued functions using kernel sums-of-squares. CoRR Boris Muzellec, Francis R. Bach, Alessandro Rudi
2021	J	`jnl`	Max-Margin is Dead, Long Live Max-Margin! CoRR Alex Nowak-Vila, Alessandro Rudi, Francis R. Bach
2021	A*	`conf`	Mixability made efficient: Fast online multiclass logistic regression. NeurIPS Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi
2021	J	`jnl`	Mixability made efficient: Fast online multiclass logistic regression. CoRR Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi
2021	J	`jnl`	Near-optimal estimation of smooth transport maps with kernel sums-of-squares. CoRR Boris Muzellec, Adrien Vacher, Francis R. Bach, François-Xavier Vialard, Alessandro Rudi
2021	J	`jnl`	Online nonparametric regression with Sobolev kernels. CoRR Oleksandr Zadorozhnyi, Pierre Gaillard, Sébastien Gerchinovitz, Alessandro Rudi
2021	A*	`conf`	Overcoming the curse of dimensionality with Laplacian regularization in semi-supervised learning. NeurIPS Vivien Cabannes, Loucas Pillaud-Vivien, Francis R. Bach, Alessandro Rudi
2021	A*	`conf`	PSD Representations for Effective Probability Models. NeurIPS Alessandro Rudi, Carlo Ciliberto
2021	J	`jnl`	PSD Representations for Effective Probability Models. CoRR Alessandro Rudi, Carlo Ciliberto
2021	J	`jnl`	Sampling from Arbitrary Functions via PSD Models. CoRR Ulysse Marteau-Ferey, Francis R. Bach, Alessandro Rudi
2020	J	`jnl`	A General Framework for Consistent Structured Prediction with Implicit Loss Embeddings. CoRR Carlo Ciliberto, Lorenzo Rosasco, Alessandro Rudi
2020	J	`jnl`	A General Framework for Consistent Structured Prediction with Implicit Loss Embeddings. J. Mach. Learn. Res. Carlo Ciliberto, Lorenzo Rosasco, Alessandro Rudi
2020	J	`jnl`	Approximating Hamiltonian dynamics with the Nyström method. Quantum Alessandro Rudi, Leonard Wossnig, Carlo Ciliberto, Andrea Rocchetto, Massimiliano Pontil, Simone Severini
2020	A*	`conf`	Consistent Structured Prediction with Max-Min Margin Markov Networks. ICML Alex Nowak, Francis R. Bach, Alessandro Rudi
2020	J	`jnl`	Consistent Structured Prediction with Max-Min Margin Markov Networks. CoRR Alex Nowak-Vila, Francis R. Bach, Alessandro Rudi
2020	A*	`conf`	Efficient improper learning for online logistic regression. COLT Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi
2020	J	`jnl`	Efficient improper learning for online logistic regression. CoRR Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi
2020	J	`jnl`	Fast quantum learning with statistical guarantees. CoRR Carlo Ciliberto, Andrea Rocchetto, Alessandro Rudi, Leonard Wossnig
2020	J	`jnl`	Faster Kriging: Facing High-Dimensional Simulators. Oper. Res. Xuefei Lu, Alessandro Rudi, Emanuele Borgonovo, Lorenzo Rosasco
2020	J	`jnl`	Finding Global Minima via Kernel Approximations. CoRR Alessandro Rudi, Ulysse Marteau-Ferey, Francis R. Bach
2020	A	`conf`	Gain with no Pain: Efficiency of Kernel-PCA by Nyström Sampling. AISTATS Nicholas Sterge, Bharath K. Sriperumbudur, Lorenzo Rosasco, Alessandro Rudi
2020	A*	`conf`	Kernel Methods Through the Roof: Handling Billions of Points Efficiently. NeurIPS Giacomo Meanti, Luigi Carratino, Lorenzo Rosasco, Alessandro Rudi
2020	J	`jnl`	Kernel methods through the roof: handling billions of points efficiently. CoRR Giacomo Meanti, Luigi Carratino, Lorenzo Rosasco, Alessandro Rudi
2020	J	`jnl`	Learning Output Embeddings in Structured Prediction. CoRR Luc Brogat-Motte, Alessandro Rudi, Céline Brouard, Juho Rousu, Florence d'Alché-Buc
2020	A*	`conf`	Non-parametric Models for Non-negative Functions. NeurIPS Ulysse Marteau-Ferey, Francis R. Bach, Alessandro Rudi
2020	J	`jnl`	Non-parametric Models for Non-negative Functions. CoRR Ulysse Marteau-Ferey, Francis R. Bach, Alessandro Rudi
2020	A	`conf`	Statistical Estimation of the Poincaré constant and Application to Sampling Multimodal Distributions. AISTATS Loucas Pillaud-Vivien, Francis R. Bach, Tony Lelièvre, Alessandro Rudi, Gabriel Stoltz
2020	A*	`conf`	Structured Prediction with Partial Labelling through the Infimum Loss. ICML Vivien Cabannes, Alessandro Rudi, Francis R. Bach
2020	J	`jnl`	Structured Prediction with Partial Labelling through the Infimum Loss. CoRR Vivien Cabannes, Alessandro Rudi, Francis R. Bach
2020	J	`jnl`	Structured and Localized Image Restoration. CoRR Thomas Eboli, Alex Nowak-Vila, Jian Sun, Francis R. Bach, Jean Ponce, Alessandro Rudi
2019	J	`jnl`	A General Theory for Structured Prediction with Smooth Convex Surrogates. CoRR Alex Nowak-Vila, Francis R. Bach, Alessandro Rudi
2019	A*	`conf`	Affine Invariant Covariance Estimation for Heavy-Tailed Distributions. COLT Dmitrii M. Ostrovskii, Alessandro Rudi
2019	A*	`conf`	Beyond Least-Squares: Fast Rates for Regularized Empirical Risk Minimization through Self-Concordance. COLT Ulysse Marteau-Ferey, Dmitrii Ostrovskii, Francis R. Bach, Alessandro Rudi
2019	J	`jnl`	Beyond Least-Squares: Fast Rates for Regularized Empirical Risk Minimization through Self-Concordance. CoRR Ulysse Marteau-Ferey, Dmitrii Ostrovskii, Francis R. Bach, Alessandro Rudi
2019	A*	`conf`	Efficient online learning with kernels for adversarial large scale problems. NeurIPS Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi
2019	J	`jnl`	Efficient online learning with kernels for adversarial large scale problems. CoRR Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi
2019	J	`jnl`	Gain with no Pain: Efficient Kernel-PCA by Nyström Sampling. CoRR Nicholas Sterge, Bharath K. Sriperumbudur, Lorenzo Rosasco, Alessandro Rudi
2019	A*	`conf`	Globally Convergent Newton Methods for Ill-conditioned Generalized Self-concordant Losses. NeurIPS Ulysse Marteau-Ferey, Francis R. Bach, Alessandro Rudi
2019	J	`jnl`	Globally Convergent Newton Methods for Ill-conditioned Generalized Self-concordant Losses. CoRR Ulysse Marteau-Ferey, Francis R. Bach, Alessandro Rudi
2019	A*	`conf`	Localized Structured Prediction. NeurIPS Carlo Ciliberto, Francis R. Bach, Alessandro Rudi
2019	A*	`conf`	Massively scalable Sinkhorn distances via the Nyström method. NeurIPS Jason M. Altschuler, Francis R. Bach, Alessandro Rudi, Jonathan Niles-Weed
2019	A	`conf`	Sharp Analysis of Learning with Discrete Losses. AISTATS Alex Nowak-Vila, Francis R. Bach, Alessandro Rudi
2018	J	`jnl`	Approximating Hamiltonian dynamics with the Nyström method. CoRR Alessandro Rudi, Leonard Wossnig, Carlo Ciliberto, Andrea Rocchetto, Massimiliano Pontil, Simone Severini
2018	J	`jnl`	Approximating the Quadratic Transportation Metric in Near-Linear Time. CoRR Jason M. Altschuler, Francis R. Bach, Alessandro Rudi, Jonathan Weed
2018	A*	`conf`	Differential Properties of Sinkhorn Approximation for Learning with Wasserstein Distance. NeurIPS Giulia Luise, Alessandro Rudi, Massimiliano Pontil, Carlo Ciliberto
2018	J	`jnl`	Differential Properties of Sinkhorn Approximation for Learning with Wasserstein Distance. CoRR Giulia Luise, Alessandro Rudi, Massimiliano Pontil, Carlo Ciliberto
2018	A*	`conf`	Exponential Convergence of Testing Error for Stochastic Gradient Methods. COLT Loucas Pillaud-Vivien, Alessandro Rudi, Francis R. Bach
2018	A*	`conf`	Learning with SGD and Random Features. NeurIPS Luigi Carratino, Alessandro Rudi, Lorenzo Rosasco
2018	J	`jnl`	Learning with SGD and Random Features. CoRR Luigi Carratino, Alessandro Rudi, Lorenzo Rosasco
2018	J	`jnl`	Localized Structured Prediction. CoRR Carlo Ciliberto, Francis R. Bach, Alessandro Rudi
2018	A*	`conf`	Manifold Structured Prediction. NeurIPS Alessandro Rudi, Carlo Ciliberto, Gian Maria Marconi, Lorenzo Rosasco
2018	J	`jnl`	Manifold Structured Prediction. CoRR Alessandro Rudi, Carlo Ciliberto, Gian Maria Marconi, Lorenzo Rosasco
2018	J	`jnl`	Massively scalable Sinkhorn distances via the Nyström method. CoRR Jason M. Altschuler, Francis R. Bach, Alessandro Rudi, Jonathan Weed
2018	A*	`conf`	On Fast Leverage Score Sampling and Optimal Learning. NeurIPS Alessandro Rudi, Daniele Calandriello, Luigi Carratino, Lorenzo Rosasco
2018	J	`jnl`	On Fast Leverage Score Sampling and Optimal Learning. CoRR Alessandro Rudi, Daniele Calandriello, Luigi Carratino, Lorenzo Rosasco
2018	J	`jnl`	Sharp Analysis of Learning with Discrete Losses. CoRR Alex Nowak-Vila, Francis R. Bach, Alessandro Rudi
2018	A*	`conf`	Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems through Multiple Passes. NeurIPS Loucas Pillaud-Vivien, Alessandro Rudi, Francis R. Bach
2018	J	`jnl`	Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems through Multiple Passes. CoRR Loucas Pillaud-Vivien, Alessandro Rudi, Francis R. Bach
2017	—	`conf`	Consistent Multitask Learning with Nonlinear Output Relations. NIPS Carlo Ciliberto, Alessandro Rudi, Lorenzo Rosasco, Massimiliano Pontil
2017	J	`jnl`	Consistent Multitask Learning with Nonlinear Output Relations. CoRR Carlo Ciliberto, Alessandro Rudi, Lorenzo Rosasco, Massimiliano Pontil
2017	J	`jnl`	Exponential convergence of testing error for stochastic gradient methods. CoRR Loucas Pillaud-Vivien, Alessandro Rudi, Francis R. Bach
2017	—	`conf`	FALKON: An Optimal Large Scale Kernel Method. NIPS Alessandro Rudi, Luigi Carratino, Lorenzo Rosasco
2017	J	`jnl`	FALKON: An Optimal Large Scale Kernel Method. CoRR Alessandro Rudi, Luigi Carratino, Lorenzo Rosasco
2017	—	`conf`	Generalization Properties of Learning with Random Features. NIPS Alessandro Rudi, Lorenzo Rosasco
2017	J	`jnl`	Regularized Kernel Algorithms for Support Estimation. Frontiers Appl. Math. Stat. Alessandro Rudi, Ernesto De Vito, Alessandro Verri, Francesca Odone
2016	—	`conf`	A Consistent Regularization Approach for Structured Prediction. NIPS Carlo Ciliberto, Lorenzo Rosasco, Alessandro Rudi
2016	J	`jnl`	A Consistent Regularization Approach for Structured Prediction. CoRR Carlo Ciliberto, Alessandro Rudi, Lorenzo Rosasco
2016	J	`jnl`	Generalization Properties of Learning with Random Features. CoRR Alessandro Rudi, Raffaello Camoriano, Lorenzo Rosasco
2016	A	`conf`	NYTRO: When Subsampling Meets Early Stopping. AISTATS Raffaello Camoriano, Tomás Angles, Alessandro Rudi, Lorenzo Rosasco
2015	—	`conf`	Less is More: Nyström Computational Regularization. NIPS Alessandro Rudi, Raffaello Camoriano, Lorenzo Rosasco
2015	J	`jnl`	Less is More: Nyström Computational Regularization. CoRR Alessandro Rudi, Raffaello Camoriano, Lorenzo Rosasco
2014	J	`jnl`	Geometrical and computational aspects of Spectral Support Estimation for novelty detection. Pattern Recognit. Lett. Alessandro Rudi, Francesca Odone, Ernesto De Vito
2013	—	`conf`	On the Sample Complexity of Subspace Learning. NIPS Alessandro Rudi, Guillermo D. Cañas, Lorenzo Rosasco
2012	B	`conf`	Adaptive Optimization for Cross Validation. ESANN Alessandro Rudi, Gabriele Chiusano, Alessandro Verri
2011	A*	`conf`	A general method for the point of regard estimation in 3D space. CVPR Fiora Pirri, Matia Pizzoli, Alessandro Rudi
2010	—	`conf`	Linear Solvability in the Viewing Graph. ACCV (3) Alessandro Rudi, Matia Pizzoli, Fiora Pirri