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ORCIDAlessandro Rudi
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2020 – today
- 2024
[j9]Ulysse Marteau-Ferey, Francis R. Bach, Alessandro Rudi
:
Second Order Conditions to Decompose Smooth Functions as Sums of Squares. SIAM J. Optim. 34(1): 616-641 (2024)- [j8]Adrien Vacher, Boris Muzellec, Francis R. Bach, François-Xavier Vialard, Alessandro Rudi:
Optimal Estimation of Smooth Transport Maps with Kernel SoS. SIAM J. Math. Data Sci. 6(2): 311-342 (2024) - [i56]Théophile Cantelobre, Carlo Ciliberto, Benjamin Guedj, Alessandro Rudi:
Closed-form Filtering for Non-linear Systems. CoRR abs/2402.09796 (2024) - [i55]Pierre Boudart, Alessandro Rudi, Pierre Gaillard:
Structured Prediction in Online Learning. CoRR abs/2406.12366 (2024) - [i54]Pierre-Cyril Aubin-Frankowski, Yohann De Castro, Axel Parmentier, Alessandro Rudi:
Generalization Bounds of Surrogate Policies for Combinatorial Optimization Problems. CoRR abs/2407.17200 (2024) - [i53]Luc Brogat-Motte, Riccardo Bonalli, Alessandro Rudi:
Learning Controlled Stochastic Differential Equations. CoRR abs/2411.01982 (2024) - 2023
- [j7]Francis R. Bach, Alessandro Rudi:
Exponential Convergence of Sum-of-Squares Hierarchies for Trigonometric Polynomials. SIAM J. Optim. 33(3): 2137-2159 (2023) - [c47]Gaspard Beugnot, Julien Mairal, Alessandro Rudi:
GloptiNets: Scalable Non-Convex Optimization with Certificates. NeurIPS 2023 - [c46]Anant Raj, Umut Simsekli, Alessandro Rudi:
Efficient Sampling of Stochastic Differential Equations with Positive Semi-Definite Models. NeurIPS 2023 - [i52]Pierre-Cyril Aubin-Frankowski, Alessandro Rudi:
Approximation of optimization problems with constraints through kernel Sum-Of-Squares. CoRR abs/2301.06339 (2023) - [i51]Anant Raj, Umut Simsekli, Alessandro Rudi:
Efficient Sampling of Stochastic Differential Equations with Positive Semi-Definite Models. CoRR abs/2303.17109 (2023) - [i50]Riccardo Bonalli, Alessandro Rudi:
Non-Parametric Learning of Stochastic Differential Equations with Fast Rates of Convergence. CoRR abs/2305.15557 (2023) - [i49]Gaspard Beugnot, Julien Mairal, Alessandro Rudi:
GloptiNets: Scalable Non-Convex Optimization with Certificates. CoRR abs/2306.14932 (2023) - 2022
- [j6]Luc Brogat-Motte, Alessandro Rudi, Céline Brouard, Juho Rousu, Florence d'Alché-Buc:
Vector-Valued Least-Squares Regression under Output Regularity Assumptions. J. Mach. Learn. Res. 23: 344:1-344:50 (2022) - [c45]Ulysse Marteau-Ferey, Francis R. Bach, Alessandro Rudi:
Sampling from Arbitrary Functions via PSD Models. AISTATS 2022: 2823-2861 - [c44]Alex Nowak, Alessandro Rudi, Francis R. Bach:
On the Consistency of Max-Margin Losses. AISTATS 2022: 4612-4633 - [c43]Eloïse Berthier, Justin Carpentier, Alessandro Rudi, Francis R. Bach:
Infinite-Dimensional Sums-of-Squares for Optimal Control. CDC 2022: 577-582 - [c42]Gaspard Beugnot, Julien Mairal, Alessandro Rudi:
On the Benefits of Large Learning Rates for Kernel Methods. COLT 2022: 254-282 - [c41]Blake E. Woodworth, Francis R. Bach, Alessandro Rudi:
Non-Convex Optimization with Certificates and Fast Rates Through Kernel Sums of Squares. COLT 2022: 4620-4642 - [c40]Théophile Cantelobre, Carlo Ciliberto, Benjamin Guedj, Alessandro Rudi:
Measuring dissimilarity with diffeomorphism invariance. ICML 2022: 2572-2596 - [c39]Antoine Chatalic, Nicolas Schreuder, Lorenzo Rosasco, Alessandro Rudi:
Nyström Kernel Mean Embeddings. ICML 2022: 3006-3024 - [c38]Vivien Cabannes, Francis R. Bach, Vianney Perchet, Alessandro Rudi:
Active Labeling: Streaming Stochastic Gradients. NeurIPS 2022 - [i48]Antoine Chatalic, Nicolas Schreuder, Alessandro Rudi, Lorenzo Rosasco:
Nyström Kernel Mean Embeddings. CoRR abs/2201.13055 (2022) - [i47]Théophile Cantelobre, Carlo Ciliberto, Benjamin Guedj, Alessandro Rudi:
Measuring dissimilarity with diffeomorphism invariance. CoRR abs/2202.05614 (2022) - [i46]Gaspard Beugnot, Julien Mairal, Alessandro Rudi:
On the Benefits of Large Learning Rates for Kernel Methods. CoRR abs/2202.13733 (2022) - [i45]Blake E. Woodworth, Francis R. Bach, Alessandro Rudi:
Non-Convex Optimization with Certificates and Fast Rates Through Kernel Sums of Squares. CoRR abs/2204.04970 (2022) - [i44]Vivien Cabannes, Francis R. Bach, Vianney Perchet, Alessandro Rudi:
Active Labeling: Streaming Stochastic Gradients. CoRR abs/2205.13255 (2022) - [i43]Luc Brogat-Motte, Alessandro Rudi, Céline Brouard, Juho Rousu, Florence d'Alché-Buc:
Vector-Valued Least-Squares Regression under Output Regularity Assumptions. CoRR abs/2211.08958 (2022) - 2021
- [c37]Vivien A. Cabannes, Francis R. Bach, Alessandro Rudi:
Fast Rates for Structured Prediction. COLT 2021: 823-865 - [c36]Adrien Vacher, Boris Muzellec, Alessandro Rudi, Francis R. Bach, François-Xavier Vialard:
A Dimension-free Computational Upper-bound for Smooth Optimal Transport Estimation. COLT 2021: 4143-4173 - [c35]Vivien A. Cabannes, Francis R. Bach, Alessandro Rudi:
Disambiguation of Weak Supervision leading to Exponential Convergence rates. ICML 2021: 1147-1157 - [c34]Alessandro Rudi, Carlo Ciliberto:
PSD Representations for Effective Probability Models. NeurIPS 2021: 19411-19422 - [c33]Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi:
Mixability made efficient: Fast online multiclass logistic regression. NeurIPS 2021: 23692-23702 - [c32]Gaspard Beugnot, Julien Mairal, Alessandro Rudi:
Beyond Tikhonov: faster learning with self-concordant losses, via iterative regularization. NeurIPS 2021: 28196-28207 - [c31]Vivien Cabannes, Loucas Pillaud-Vivien, Francis R. Bach, Alessandro Rudi:
Overcoming the curse of dimensionality with Laplacian regularization in semi-supervised learning. NeurIPS 2021: 30439-30451 - [i42]Vivien Cabannes, Alessandro Rudi, Francis R. Bach:
Fast rates in structured prediction. CoRR abs/2102.00760 (2021) - [i41]Vivien Cabannes, Francis R. Bach, Alessandro Rudi:
Disambiguation of weak supervision with exponential convergence rates. CoRR abs/2102.02789 (2021) - [i40]Oleksandr Zadorozhnyi, Pierre Gaillard, Sébastien Gerchinovitz, Alessandro Rudi:
Online nonparametric regression with Sobolev kernels. CoRR abs/2102.03594 (2021) - [i39]Alex Nowak-Vila, Alessandro Rudi, Francis R. Bach:
Max-Margin is Dead, Long Live Max-Margin! CoRR abs/2105.15069 (2021) - [i38]Gaspard Beugnot, Julien Mairal, Alessandro Rudi:
Beyond Tikhonov: Faster Learning with Self-Concordant Losses via Iterative Regularization. CoRR abs/2106.08855 (2021) - [i37]Boris Muzellec, Francis R. Bach, Alessandro Rudi:
A Note on Optimizing Distributions using Kernel Mean Embeddings. CoRR abs/2106.09994 (2021) - [i36]Alessandro Rudi, Carlo Ciliberto:
PSD Representations for Effective Probability Models. CoRR abs/2106.16116 (2021) - [i35]Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi:
Mixability made efficient: Fast online multiclass logistic regression. CoRR abs/2110.03960 (2021) - [i34]Ulysse Marteau-Ferey, Francis R. Bach, Alessandro Rudi:
Sampling from Arbitrary Functions via PSD Models. CoRR abs/2110.10527 (2021) - [i33]Boris Muzellec, Francis R. Bach, Alessandro Rudi:
Learning PSD-valued functions using kernel sums-of-squares. CoRR abs/2111.11306 (2021) - [i32]Boris Muzellec, Adrien Vacher, Francis R. Bach, François-Xavier Vialard, Alessandro Rudi:
Near-optimal estimation of smooth transport maps with kernel sums-of-squares. CoRR abs/2112.01907 (2021) - 2020
- [j5]Xuefei Lu, Alessandro Rudi, Emanuele Borgonovo, Lorenzo Rosasco:
Faster Kriging: Facing High-Dimensional Simulators. Oper. Res. 68(1): 233-249 (2020) - [j4]Carlo Ciliberto, Lorenzo Rosasco, Alessandro Rudi:
A General Framework for Consistent Structured Prediction with Implicit Loss Embeddings. J. Mach. Learn. Res. 21: 98:1-98:67 (2020) - [j3]Alessandro Rudi, Leonard Wossnig, Carlo Ciliberto, Andrea Rocchetto, Massimiliano Pontil, Simone Severini:
Approximating Hamiltonian dynamics with the Nyström method. Quantum 4: 234 (2020) - [c30]Loucas Pillaud-Vivien, Francis R. Bach, Tony Lelièvre, Alessandro Rudi, Gabriel Stoltz:
Statistical Estimation of the Poincaré constant and Application to Sampling Multimodal Distributions. AISTATS 2020: 2753-2763 - [c29]Nicholas Sterge, Bharath K. Sriperumbudur, Lorenzo Rosasco, Alessandro Rudi:
Gain with no Pain: Efficiency of Kernel-PCA by Nyström Sampling. AISTATS 2020: 3642-3652 - [c28]Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi:
Efficient improper learning for online logistic regression. COLT 2020: 2085-2108 - [c27]Vivien Cabannes, Alessandro Rudi, Francis R. Bach:
Structured Prediction with Partial Labelling through the Infimum Loss. ICML 2020: 1230-1239 - [c26]Alex Nowak, Francis R. Bach, Alessandro Rudi:
Consistent Structured Prediction with Max-Min Margin Markov Networks. ICML 2020: 7381-7391 - [c25]Ulysse Marteau-Ferey, Francis R. Bach, Alessandro Rudi:
Non-parametric Models for Non-negative Functions. NeurIPS 2020 - [c24]Giacomo Meanti, Luigi Carratino, Lorenzo Rosasco, Alessandro Rudi:
Kernel Methods Through the Roof: Handling Billions of Points Efficiently. NeurIPS 2020 - [i31]Carlo Ciliberto, Andrea Rocchetto, Alessandro Rudi, Leonard Wossnig:
Fast quantum learning with statistical guarantees. CoRR abs/2001.10477 (2020) - [i30]Carlo Ciliberto, Lorenzo Rosasco, Alessandro Rudi:
A General Framework for Consistent Structured Prediction with Implicit Loss Embeddings. CoRR abs/2002.05424 (2020) - [i29]Vivien Cabannes, Alessandro Rudi, Francis R. Bach:
Structured Prediction with Partial Labelling through the Infimum Loss. CoRR abs/2003.00920 (2020) - [i28]Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi:
Efficient improper learning for online logistic regression. CoRR abs/2003.08109 (2020) - [i27]Thomas Eboli, Alex Nowak-Vila, Jian Sun, Francis R. Bach, Jean Ponce, Alessandro Rudi:
Structured and Localized Image Restoration. CoRR abs/2006.09261 (2020) - [i26]Giacomo Meanti, Luigi Carratino, Lorenzo Rosasco, Alessandro Rudi:
Kernel methods through the roof: handling billions of points efficiently. CoRR abs/2006.10350 (2020) - [i25]Alex Nowak-Vila, Francis R. Bach, Alessandro Rudi:
Consistent Structured Prediction with Max-Min Margin Markov Networks. CoRR abs/2007.01012 (2020) - [i24]Ulysse Marteau-Ferey, Francis R. Bach, Alessandro Rudi:
Non-parametric Models for Non-negative Functions. CoRR abs/2007.03926 (2020) - [i23]Luc Brogat-Motte, Alessandro Rudi, Céline Brouard, Juho Rousu, Florence d'Alché-Buc:
Learning Output Embeddings in Structured Prediction. CoRR abs/2007.14703 (2020) - [i22]Alessandro Rudi, Ulysse Marteau-Ferey, Francis R. Bach:
Finding Global Minima via Kernel Approximations. CoRR abs/2012.11978 (2020)
2010 – 2019
- 2019
- [c23]Alex Nowak-Vila, Francis R. Bach, Alessandro Rudi:
Sharp Analysis of Learning with Discrete Losses. AISTATS 2019: 1920-1929 - [c22]Ulysse Marteau-Ferey, Dmitrii Ostrovskii, Francis R. Bach, Alessandro Rudi:
Beyond Least-Squares: Fast Rates for Regularized Empirical Risk Minimization through Self-Concordance. COLT 2019: 2294-2340 - [c21]Dmitrii M. Ostrovskii, Alessandro Rudi:
Affine Invariant Covariance Estimation for Heavy-Tailed Distributions. COLT 2019: 2531-2550 - [c20]Jason M. Altschuler, Francis R. Bach, Alessandro Rudi, Jonathan Niles-Weed:
Massively scalable Sinkhorn distances via the Nyström method. NeurIPS 2019: 4429-4439 - [c19]Carlo Ciliberto, Francis R. Bach, Alessandro Rudi:
Localized Structured Prediction. NeurIPS 2019: 7299-7309 - [c18]Ulysse Marteau-Ferey, Francis R. Bach, Alessandro Rudi:
Globally Convergent Newton Methods for Ill-conditioned Generalized Self-concordant Losses. NeurIPS 2019: 7634-7644 - [c17]Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi:
Efficient online learning with kernels for adversarial large scale problems. NeurIPS 2019: 9427-9436 - [i21]Alex Nowak-Vila, Francis R. Bach, Alessandro Rudi:
A General Theory for Structured Prediction with Smooth Convex Surrogates. CoRR abs/1902.01958 (2019) - [i20]Ulysse Marteau-Ferey, Dmitrii Ostrovskii, Francis R. Bach, Alessandro Rudi:
Beyond Least-Squares: Fast Rates for Regularized Empirical Risk Minimization through Self-Concordance. CoRR abs/1902.03046 (2019) - [i19]Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi:
Efficient online learning with kernels for adversarial large scale problems. CoRR abs/1902.09917 (2019) - [i18]Ulysse Marteau-Ferey, Francis R. Bach, Alessandro Rudi:
Globally Convergent Newton Methods for Ill-conditioned Generalized Self-concordant Losses. CoRR abs/1907.01771 (2019) - [i17]Nicholas Sterge, Bharath K. Sriperumbudur, Lorenzo Rosasco, Alessandro Rudi:
Gain with no Pain: Efficient Kernel-PCA by Nyström Sampling. CoRR abs/1907.05226 (2019) - 2018
- [c16]Loucas Pillaud-Vivien, Alessandro Rudi, Francis R. Bach:
Exponential Convergence of Testing Error for Stochastic Gradient Methods. COLT 2018: 250-296 - [c15]Alessandro Rudi, Carlo Ciliberto, Gian Maria Marconi, Lorenzo Rosasco:
Manifold Structured Prediction. NeurIPS 2018: 5615-5626 - [c14]Alessandro Rudi, Daniele Calandriello, Luigi Carratino, Lorenzo Rosasco:
On Fast Leverage Score Sampling and Optimal Learning. NeurIPS 2018: 5677-5687 - [c13]Giulia Luise, Alessandro Rudi, Massimiliano Pontil, Carlo Ciliberto:
Differential Properties of Sinkhorn Approximation for Learning with Wasserstein Distance. NeurIPS 2018: 5864-5874 - [c12]Loucas Pillaud-Vivien, Alessandro Rudi, Francis R. Bach:
Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems through Multiple Passes. NeurIPS 2018: 8125-8135 - [c11]Luigi Carratino, Alessandro Rudi, Lorenzo Rosasco:
Learning with SGD and Random Features. NeurIPS 2018: 10213-10224 - [i16]Alessandro Rudi, Leonard Wossnig, Carlo Ciliberto, Andrea Rocchetto, Massimiliano Pontil, Simone Severini:
Approximating Hamiltonian dynamics with the Nyström method. CoRR abs/1804.02484 (2018) - [i15]Loucas Pillaud-Vivien, Alessandro Rudi, Francis R. Bach:
Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems through Multiple Passes. CoRR abs/1805.10074 (2018) - [i14]Giulia Luise, Alessandro Rudi, Massimiliano Pontil, Carlo Ciliberto:
Differential Properties of Sinkhorn Approximation for Learning with Wasserstein Distance. CoRR abs/1805.11897 (2018) - [i13]Carlo Ciliberto, Francis R. Bach, Alessandro Rudi:
Localized Structured Prediction. CoRR abs/1806.02402 (2018) - [i12]Alessandro Rudi, Carlo Ciliberto, Gian Maria Marconi, Lorenzo Rosasco:
Manifold Structured Prediction. CoRR abs/1806.09908 (2018) - [i11]Luigi Carratino, Alessandro Rudi, Lorenzo Rosasco:
Learning with SGD and Random Features. CoRR abs/1807.06343 (2018) - [i10]Alex Nowak-Vila, Francis R. Bach, Alessandro Rudi:
Sharp Analysis of Learning with Discrete Losses. CoRR abs/1810.06839 (2018) - [i9]Jason M. Altschuler, Francis R. Bach, Alessandro Rudi, Jonathan Weed:
Approximating the Quadratic Transportation Metric in Near-Linear Time. CoRR abs/1810.10046 (2018) - [i8]Alessandro Rudi, Daniele Calandriello, Luigi Carratino, Lorenzo Rosasco:
On Fast Leverage Score Sampling and Optimal Learning. CoRR abs/1810.13258 (2018) - [i7]Jason M. Altschuler, Francis R. Bach, Alessandro Rudi, Jonathan Weed:
Massively scalable Sinkhorn distances via the Nyström method. CoRR abs/1812.05189 (2018) - 2017
- [j2]Alessandro Rudi, Ernesto De Vito, Alessandro Verri, Francesca Odone:
Regularized Kernel Algorithms for Support Estimation. Frontiers Appl. Math. Stat. 3: 23 (2017) - [c10]Carlo Ciliberto, Alessandro Rudi, Lorenzo Rosasco, Massimiliano Pontil:
Consistent Multitask Learning with Nonlinear Output Relations. NIPS 2017: 1986-1996 - [c9]Alessandro Rudi, Lorenzo Rosasco:
Generalization Properties of Learning with Random Features. NIPS 2017: 3215-3225 - [c8]Alessandro Rudi, Luigi Carratino, Lorenzo Rosasco:
FALKON: An Optimal Large Scale Kernel Method. NIPS 2017: 3888-3898 - [i6]Carlo Ciliberto, Alessandro Rudi, Lorenzo Rosasco, Massimiliano Pontil:
Consistent Multitask Learning with Nonlinear Output Relations. CoRR abs/1705.08118 (2017) - [i5]Alessandro Rudi, Luigi Carratino, Lorenzo Rosasco:
FALKON: An Optimal Large Scale Kernel Method. CoRR abs/1705.10958 (2017) - [i4]Loucas Pillaud-Vivien, Alessandro Rudi, Francis R. Bach:
Exponential convergence of testing error for stochastic gradient methods. CoRR abs/1712.04755 (2017) - 2016
- [c7]Raffaello Camoriano, Tomás Angles, Alessandro Rudi, Lorenzo Rosasco:
NYTRO: When Subsampling Meets Early Stopping. AISTATS 2016: 1403-1411 - [c6]Carlo Ciliberto, Lorenzo Rosasco, Alessandro Rudi:
A Consistent Regularization Approach for Structured Prediction. NIPS 2016: 4412-4420 - [i3]Alessandro Rudi, Raffaello Camoriano, Lorenzo Rosasco:
Generalization Properties of Learning with Random Features. CoRR abs/1602.04474 (2016) - [i2]Carlo Ciliberto, Alessandro Rudi, Lorenzo Rosasco:
A Consistent Regularization Approach for Structured Prediction. CoRR abs/1605.07588 (2016) - 2015
- [c5]Alessandro Rudi, Raffaello Camoriano, Lorenzo Rosasco:
Less is More: Nyström Computational Regularization. NIPS 2015: 1657-1665 - [i1]Alessandro Rudi, Raffaello Camoriano, Lorenzo Rosasco:
Less is More: Nyström Computational Regularization. CoRR abs/1507.04717 (2015) - 2014
- [j1]Alessandro Rudi, Francesca Odone, Ernesto De Vito:
Geometrical and computational aspects of Spectral Support Estimation for novelty detection. Pattern Recognit. Lett. 36: 107-116 (2014) - 2013
- [c4]Alessandro Rudi, Guillermo D. Cañas, Lorenzo Rosasco:
On the Sample Complexity of Subspace Learning. NIPS 2013: 2067-2075 - 2012
- [c3]Alessandro Rudi, Gabriele Chiusano, Alessandro Verri:
Adaptive Optimization for Cross Validation. ESANN 2012 - 2011
- [c2]Fiora Pirri, Matia Pizzoli, Alessandro Rudi:
A general method for the point of regard estimation in 3D space. CVPR 2011: 921-928 - 2010
- [c1]Alessandro Rudi, Matia Pizzoli, Fiora Pirri:
Linear Solvability in the Viewing Graph. ACCV (3) 2010: 369-381
Coauthor Index
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