Iterative Regularization for Learning with Convex Loss Functions

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Iterative Regularization for Learning with Convex Loss Functions

31 March 2015

Lorenzo Rosasco

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Papers citing "Iterative Regularization for Learning with Convex Loss Functions"

19 / 19 papers shown

Title
Towards Weaker Variance Assumptions for Stochastic Optimization Ahmet Alacaoglu Yura Malitsky Stephen J. Wright 84 1 0 14 Apr 2025
Lp- and Risk Consistency of Localized SVMs Hannes Köhler 119 0 0 16 May 2023
Random Smoothing Regularization in Kernel Gradient Descent Learning Liang Ding Tianyang Hu Jiahan Jiang Donghao Li Wei Cao Yuan Yao 74 6 0 05 May 2023
Iterative regularization in classification via hinge loss diagonal descent Vassilis Apidopoulos T. Poggio Lorenzo Rosasco S. Villa 65 2 0 24 Dec 2022
Exponential Tail Local Rademacher Complexity Risk Bounds Without the Bernstein Condition Varun Kanade Patrick Rebeschini Tomas Vaskevicius 78 10 0 23 Feb 2022
From inexact optimization to learning via gradient concentration Bernhard Stankewitz Nicole Mücke Lorenzo Rosasco 88 5 0 09 Jun 2021
Learning with Gradient Descent and Weakly Convex Losses Dominic Richards Michael G. Rabbat MLT 71 15 0 13 Jan 2021
The Statistical Complexity of Early-Stopped Mirror Descent Tomas Vaskevicius Varun Kanade Patrick Rebeschini 90 23 0 01 Feb 2020
Large-scale Kernel Methods and Applications to Lifelong Robot Learning Raffaello Camoriano 84 1 0 11 Dec 2019
Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification Chen Wang Qin Yu Kai Zhou D. Hui Xiaofeng Gong Ruisen Luo 141 22 0 09 Aug 2019
Improved Classification Rates for Localized SVMs Ingrid Blaschzyk Ingo Steinwart 47 5 0 04 May 2019
Graph-Dependent Implicit Regularisation for Distributed Stochastic Subgradient Descent Dominic Richards Patrick Rebeschini 73 18 0 18 Sep 2018
Proximal boosting: aggregating weak learners to minimize non-differentiable losses Erwan Fouillen C. Boyer Maxime Sangnier FedML 75 2 0 29 Aug 2018
Efficacy of regularized multi-task learning based on SVM models Shaohan Chen Zhou Fang Sijie Lu Chuanhou Gao 25 9 0 31 May 2018
Optimal Rates for Learning with Nyström Stochastic Gradient Methods Junhong Lin Lorenzo Rosasco 98 7 0 21 Oct 2017
Spatial Decompositions for Large Scale SVMs P. Thomann Ingrid Blaschzyk Mona Meister Ingo Steinwart 56 21 0 01 Dec 2016
Distributed learning with regularized least squares Shaobo Lin Xin Guo Ding-Xuan Zhou 186 191 0 11 Aug 2016
Alternative asymptotics for cointegration tests in large VARs Junhong Lin Lorenzo Rosasco 72 37 0 28 May 2016
Generalization Properties and Implicit Regularization for Multiple Passes SGM Junhong Lin Raffaello Camoriano Lorenzo Rosasco 81 70 0 26 May 2016