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1902.03046
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Beyond Least-Squares: Fast Rates for Regularized Empirical Risk Minimization through Self-Concordance
8 February 2019
Ulysse Marteau-Ferey
Dmitrii Ostrovskii
Francis R. Bach
Alessandro Rudi
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Papers citing
"Beyond Least-Squares: Fast Rates for Regularized Empirical Risk Minimization through Self-Concordance"
38 / 38 papers shown
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30 Jul 2023
Doubly Stochastic Models: Learning with Unbiased Label Noises and Inference Stability
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Fast kernel methods for Data Quality Monitoring as a goodness-of-fit test
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Confidence Sets under Generalized Self-Concordance
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231
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31 Dec 2022
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Sobolev Acceleration and Statistical Optimality for Learning Elliptic Equations via Gradient Descent
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Yiping Lu
Jose H. Blanchet
Lexing Ying
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Learning new physics efficiently with nonparametric methods
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Gianvito Losapio
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A. Wulzer
M. Pierini
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Lorenzo Rosasco
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Error Scaling Laws for Kernel Classification under Source and Capacity Conditions
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Lenka Zdeborová
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Alberto Bemporad
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Kernel-based estimation for partially functional linear model: Minimax rates and randomized sketches
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Mixability made efficient: Fast online multiclass logistic regression
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Pierre Gaillard
Alessandro Rudi
247
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Efficient Methods for Online Multiclass Logistic Regression
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Satyen Kale
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283
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Beyond Tikhonov: Faster Learning with Self-Concordant Losses via Iterative Regularization
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182
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16 Jun 2021
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257
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Annals of Statistics (Ann. Stat.), 2021
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Fast rates in structured prediction
Annual Conference Computational Learning Theory (COLT), 2021
Vivien A. Cabannes
Alessandro Rudi
Francis R. Bach
671
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01 Feb 2021
Near-Optimal Procedures for Model Discrimination with Non-Disclosure Properties
Dmitrii Ostrovskii
M. Ndaoud
Adel Javanmard
Meisam Razaviyayn
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429
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Towards Optimal Problem Dependent Generalization Error Bounds in Statistical Learning Theory
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A. Zeevi
536
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Kernel methods through the roof: handling billions of points efficiently
Giacomo Meanti
Luigi Carratino
Lorenzo Rosasco
Alessandro Rudi
505
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Kernel Alignment Risk Estimator: Risk Prediction from Training Data
Arthur Jacot
Berfin cSimcsek
Francesco Spadaro
Clément Hongler
Franck Gabriel
304
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17 Jun 2020
On the Estimation of Derivatives Using Plug-in Kernel Ridge Regression Estimators
Journal of machine learning research (JMLR), 2020
Zejian Liu
Meng Li
405
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Efficient improper learning for online logistic regression
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Rémi Jézéquel
Pierre Gaillard
Alessandro Rudi
315
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18 Mar 2020
A Spectral Analysis of Dot-product Kernels
M. Scetbon
Zaïd Harchaoui
925
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28 Feb 2020
Implicit Regularization of Random Feature Models
International Conference on Machine Learning (ICML), 2020
Arthur Jacot
Berfin Simsek
Francesco Spadaro
Clément Hongler
Franck Gabriel
373
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19 Feb 2020
Self-Concordant Analysis of Frank-Wolfe Algorithms
International Conference on Machine Learning (ICML), 2020
Pavel Dvurechensky
P. Ostroukhov
K. Safin
Shimrit Shtern
Mathias Staudigl
401
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An improper estimator with optimal excess risk in misspecified density estimation and logistic regression
Journal of machine learning research (JMLR), 2019
Jaouad Mourtada
Stéphane Gaïffas
376
34
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Fast and Furious Convergence: Stochastic Second Order Methods under Interpolation
International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
S. Meng
Sharan Vaswani
I. Laradji
Mark Schmidt
Damien Scieur
326
39
0
11 Oct 2019
Globally Convergent Newton Methods for Ill-conditioned Generalized Self-concordant Losses
Ulysse Marteau-Ferey
Francis R. Bach
Alessandro Rudi
282
41
0
03 Jul 2019
Finite-sample analysis of M-estimators using self-concordance
Dmitrii Ostrovskii
Francis R. Bach
287
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