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	Pour les 42 documents Envoyer sur ORCID RSS ATOM Exporter BibTeX XML-TEI CSV RTF EndNote PDF HTML Export avancé	Page : Page précédente 1 2 Page suivante	triés par Pertinence Auteur A→Z Auteur Z→A Titre A→Z Titre Z→A Date de publication croissante Date de publication décroissante Date de dépôt croissante Date de dépôt décroissante

		Exponential convergence of testing error for stochastic gradient methods Loucas Pillaud-Vivien , Alessandro Rudi , Francis Bach Conference on Learning Theory (COLT), Jul 2018, Stockholm, Sweden Communication dans un congrès hal-01662278v3	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Statistical Estimation of the Poincaré constant and Application to Sampling Multimodal Distributions Loucas Pillaud-Vivien , Francis Bach , Tony Lelièvre , Alessandro Rudi , Gabriel Stoltz AISTATS 2020 : 23rd International Conference on Artificial Intelligence and Statistics, Jun 2020, Palermo / Virtual, Italy Communication dans un congrès hal-02327453v3	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		A Dimension-free Computational Upper-bound for Smooth Optimal Transport Estimation Adrien Vacher , Boris Muzellec , Alessandro Rudi , Francis Bach , François-Xavier Vialard COLT 2021 - 34th Annual Conference on Learning Theory, Aug 2021, Boulder, United States Communication dans un congrès hal-03454237v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Non-parametric Models for Non-negative Functions Ulysse Marteau-Ferey , Francis Bach , Alessandro Rudi 2020 Pré-publication, Document de travail hal-02891640v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Localized Structured Prediction Carlo Ciliberto , Francis Bach , Alessandro Rudi 2018 Pré-publication, Document de travail hal-01958863v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Non-Convex Optimization with Certificates and Fast Rates Through Kernel Sums of Squares Blake Woodworth , Francis Bach , Alessandro Rudi Conference on Learning Theory 2022, Jul 2022, London, United Kingdom. pp.4620-4642, ⟨10.48550/arXiv.2204.04970⟩ Communication dans un congrès hal-03635236v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Efficient improper learning for online logistic regression Rémi Jézéquel , Pierre Gaillard , Alessandro Rudi COLT 2020 - 33rd Annual Conference on Learning Theory, Jul 2020, Graz / Virtual, Austria Communication dans un congrès hal-02510505v3	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		A Note on Optimizing Distributions using Kernel Mean Embeddings Boris Muzellec , Francis Bach , Alessandro Rudi 2021 Pré-publication, Document de travail hal-03454259v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Manifold Structured Prediction Alessandro Rudi , Carlo Ciliberto , Gian Maria Marconi , Lorenzo Rosasco NIPS 2018 - Neural Information Processing Systems Conference, Dec 2018, Montreal, Canada. pp.5615-5626 Communication dans un congrès hal-01958900v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Affine Invariant Covariance Estimation for Heavy-Tailed Distributions Dmitrii M. Ostrovskii , Alessandro Rudi COLT 2019 - 32nd Annual Conference on Learning Theory, Jun 2019, Phoenix, United States Communication dans un congrès hal-02011464v2	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Learning Output Embeddings in Structured Prediction Luc Brogat-Motte , Alessandro Rudi , Celine Brouard , Juho Rousu , Florence d'Alché-Buc 2021 Pré-publication, Document de travail hal-03282445v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Efficient Sampling of Stochastic Differential Equations with Positive Semi-Definite Models Anant Raj , Umut Şimşekli , Alessandro Rudi NeurIPS 2023 - Thirty-seventh Annual Conference on Neural Information Processing Systems, Dec 2023, New Orleans, United States Communication dans un congrès hal-04478943v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Finding Global Minima via Kernel Approximations Alessandro Rudi , Ulysse Marteau-Ferey , Francis Bach 2020 Pré-publication, Document de travail hal-03081675v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Learning with SGD and Random Features Luigi Carratino , Alessandro Rudi , Lorenzo Rosasco Advances in Neural Information Processing Systems, Dec 2018, Montreal, Canada. pp.10213--10224 Communication dans un congrès hal-01958906v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Near-optimal estimation of smooth transport maps with kernel sums-of-squares Boris Muzellec , Adrien Vacher , Francis Bach , François-Xavier Vialard , Alessandro Rudi SIAM Journal on Mathematics of Data Science, In press Article dans une revue hal-03466696v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Non-Parametric Learning of Stochastic Differential Equations with Fast Rates of Convergence Riccardo Bonalli , Alessandro Rudi 2024 Pré-publication, Document de travail hal-04381810v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Measuring dissimilarity with diffeomorphism invariance Théophile Cantelobre , Carlo Ciliberto , Benjamin Guedj , Alessandro Rudi 2022 Pré-publication, Document de travail hal-03573479v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Sampling from Arbitrary Functions via PSD Models Ulysse Marteau-Ferey , Francis Bach , Alessandro Rudi AISTATS 2022 - 25th International Conference on Artificial Intelligence and Statistics, Mar 2022, Valencia (virtual), Spain Communication dans un congrès hal-03386544v3	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Exponential convergence of sum-of-squares hierarchies for trigonometric polynomials Francis Bach , Alessandro Rudi SIAM Journal on Optimization, In press, ⟨10.1137/22m1540818⟩ Article dans une revue hal-03843458v4	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Closed-form Filtering for Non-linear Systems Théophile Cantelobre , Carlo Ciliberto , Benjamin Guedj , Alessandro Rudi 2024 Pré-publication, Document de travail hal-04458936v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		On Fast Leverage Score Sampling and Optimal Learning Alessandro Rudi , Daniele Calandriello , Luigi Carratino , Lorenzo Rosasco NeurIPS 2018 - Thirty-second Conference on Neural Information Processing Systems, Dec 2018, Montreal, Canada. pp.5677--5687 Communication dans un congrès hal-01958879v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Efficient online learning with kernels for adversarial large scale problems Rémi Jézéquel , Pierre Gaillard , Alessandro Rudi 2019 Pré-publication, Document de travail hal-02019402v2	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Beyond Least-Squares: Fast Rates for Regularized Empirical Risk Minimization through Self-Concordance Ulysse Marteau-Ferey , Dmitrii M. Ostrovskii , Francis Bach , Alessandro Rudi 2019 Pré-publication, Document de travail hal-02011895v3	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		On the Benefits of Large Learning Rates for Kernel Methods Gaspard Beugnot , Alessandro Rudi , Julien Mairal COLT 2022 - 35th Annual Conference on Learning Theory, Jul 2022, London, United Kingdom. pp.254--282 Communication dans un congrès hal-03878527v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Mixability made efficient: Fast online multiclass logistic regression Rémi Jézéquel , Pierre Gaillard , Alessandro Rudi NeurIPS 2021. Thirty-fifth Conference on Neural Information Processing Systems, Dec 2021, Online, France Communication dans un congrès hal-03370530v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Learning PSD-valued functions using kernel sums-of-squares Boris Muzellec , Francis Bach , Alessandro Rudi 2021 Pré-publication, Document de travail hal-03454277v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Fast Rates for Structured Prediction Vivien Cabannes , Francis Bach , Alessandro Rudi COLT 2021 - 34th Annual Conference on Learning Theory, Aug 2021, Boulder, Colorado, United States Communication dans un congrès hal-03384304v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Overcoming the curse of dimensionality with Laplacian regularization in semi-supervised learning Vivien Cabannes , Loucas Pillaud-Vivien , Francis Bach , Alessandro Rudi NeurIPS 2021 - Thirty-fifth conference on Neural Information Processing Systems (NeurIPS), Dec 2021, Online, Unknown Region Communication dans un congrès hal-03454809v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Differential Properties of Sinkhorn Approximation for Learning with Wasserstein Distance Giulia Luise , Alessandro Rudi , Massimiliano Pontil , Carlo Ciliberto NIPS 2018 - Advances in Neural Information Processing Systems, Dec 2018, Montreal, Canada. pp.5864-5874 Communication dans un congrès hal-01958887v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems through Multiple Passes Loucas Pillaud-Vivien , Alessandro Rudi , Francis Bach Neural Information Processing Systems (NeurIPS), Dec 2018, Montréal, Canada Communication dans un congrès hal-01799116v4	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More

Filtrer vos résultats

Exponential convergence of testing error for stochastic gradient methods

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

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

Non-parametric Models for Non-negative Functions

Localized Structured Prediction

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

Efficient improper learning for online logistic regression

A Note on Optimizing Distributions using Kernel Mean Embeddings

Manifold Structured Prediction

Affine Invariant Covariance Estimation for Heavy-Tailed Distributions

Learning Output Embeddings in Structured Prediction

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

Finding Global Minima via Kernel Approximations

Learning with SGD and Random Features

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

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

Measuring dissimilarity with diffeomorphism invariance

Sampling from Arbitrary Functions via PSD Models

Exponential convergence of sum-of-squares hierarchies for trigonometric polynomials

Closed-form Filtering for Non-linear Systems

On Fast Leverage Score Sampling and Optimal Learning

Efficient online learning with kernels for adversarial large scale problems

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

On the Benefits of Large Learning Rates for Kernel Methods

Mixability made efficient: Fast online multiclass logistic regression

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

Fast Rates for Structured Prediction

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

Differential Properties of Sinkhorn Approximation for Learning with Wasserstein Distance

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