Simultaneous Model Selection and Optimization through Parameter-free Stochastic Learning

15 June 2014

Papers citing "Simultaneous Model Selection and Optimization through Parameter-free Stochastic Learning"

48 / 48 papers shown

Title
LightSAM: Parameter-Agnostic Sharpness-Aware Minimization Yifei Cheng Li Shen Hao Sun Nan Yin Xiaochun Cao Enhong Chen AAML 44 0 0 30 May 2025
Efficiently Solving Discounted MDPs with Predictions on Transition Matrices Lixing Lyu Jiashuo Jiang Wang Chi Cheung 87 1 0 24 Feb 2025
Normalized Gradients for All Francesco Orabona 110 10 0 10 Aug 2023
Optimistically Tempered Online Learning Maxime Haddouche Olivier Wintenberger Benjamin Guedj OnRL 78 1 0 18 Jan 2023
Making SGD Parameter-Free Y. Carmon Oliver Hinder 98 47 0 04 May 2022
Implicit Parameter-free Online Learning with Truncated Linear Models Keyi Chen Ashok Cutkosky Francesco Orabona 80 10 0 19 Mar 2022
Parameter-free Online Linear Optimization with Side Information via Universal Coin Betting J. Jon Ryu Alankrita Bhatt Young-Han Kim 59 1 0 04 Feb 2022
Understanding AdamW through Proximal Methods and Scale-Freeness Zhenxun Zhuang Mingrui Liu Ashok Cutkosky Francesco Orabona 93 72 0 31 Jan 2022
PDE-Based Optimal Strategy for Unconstrained Online Learning Zhiyu Zhang Ashok Cutkosky I. Paschalidis 100 27 0 19 Jan 2022
Improved Learning Rates for Stochastic Optimization: Two Theoretical Viewpoints Shaojie Li Yong Liu 105 13 0 19 Jul 2021
Nonparametric Regression with Shallow Overparameterized Neural Networks Trained by GD with Early Stopping Ilja Kuzborskij Csaba Szepesvári 107 7 0 12 Jul 2021
Model Selection for Generic Contextual Bandits Avishek Ghosh Abishek Sankararaman Kannan Ramchandran 79 6 0 07 Jul 2021
MetaGrad: Adaptation using Multiple Learning Rates in Online Learning T. Erven Wouter M. Koolen Dirk van der Hoeven ODL 109 23 0 12 Feb 2021
Pareto Optimal Model Selection in Linear Bandits Yinglun Zhu Robert D. Nowak 43 14 0 12 Feb 2021
AutonoML: Towards an Integrated Framework for Autonomous Machine Learning D. Kedziora Katarzyna Musial Bogdan Gabrys 94 17 0 23 Dec 2020
Online Linear Optimization with Many Hints Aditya Bhaskara Ashok Cutkosky Ravi Kumar Manish Purohit 150 18 0 06 Oct 2020
Online Parameter-Free Learning of Multiple Low Variance Tasks Giulia Denevi Dimitris Stamos Massimiliano Pontil 99 0 0 11 Jul 2020
Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent Yunwen Lei Yiming Ying MLT 99 129 0 15 Jun 2020
Better Parameter-free Stochastic Optimization with ODE Updates for Coin-Betting K. Chen John Langford Francesco Orabona 91 22 0 12 Jun 2020
Problem-Complexity Adaptive Model Selection for Stochastic Linear Bandits Avishek Ghosh Abishek Sankararaman Kannan Ramchandran 80 34 0 04 Jun 2020
Adaptive Online Learning with Varying Norms Ashok Cutkosky 45 0 0 10 Feb 2020
Large-scale Kernel Methods and Applications to Lifelong Robot Learning Raffaello Camoriano 84 1 0 11 Dec 2019
Variance Reduced Stochastic Proximal Algorithm for AUC Maximization Soham Dan Dushyant Sahoo 106 3 0 08 Nov 2019
Stochastic Proximal AUC Maximization Yunwen Lei Yiming Ying 56 26 0 14 Jun 2019
Model selection for contextual bandits Dylan J. Foster A. Krishnamurthy Haipeng Luo OffRL 216 90 0 03 Jun 2019
Matrix-Free Preconditioning in Online Learning Ashok Cutkosky Tamás Sarlós ODL 98 16 0 29 May 2019
Combining Online Learning Guarantees Ashok Cutkosky 83 27 0 24 Feb 2019
Beating SGD Saturation with Tail-Averaging and Minibatching Nicole Mücke Gergely Neu Lorenzo Rosasco 106 37 0 22 Feb 2019
Adaptive scale-invariant online algorithms for learning linear models Michal Kempka W. Kotłowski Manfred K. Warmuth 96 31 0 20 Feb 2019
Learning with SGD and Random Features Luigi Carratino Alessandro Rudi Lorenzo Rosasco 86 78 0 17 Jul 2018
Automatic Gradient Boosting Janek Thomas Stefan Coors B. Bischl 115 23 0 10 Jul 2018
Best of many worlds: Robust model selection for online supervised learning Vidya Muthukumar Mitas Ray A. Sahai Peter L. Bartlett OffRL 80 8 0 22 May 2018
Online Learning: Sufficient Statistics and the Burkholder Method Dylan J. Foster Alexander Rakhlin Karthik Sridharan 63 27 0 20 Mar 2018
Black-Box Reductions for Parameter-free Online Learning in Banach Spaces Ashok Cutkosky Francesco Orabona 109 148 0 17 Feb 2018
Distributed Stochastic Optimization via Adaptive SGD Ashok Cutkosky R. Busa-Fekete FedML 87 21 0 16 Feb 2018
Parameter-free online learning via model selection Dylan J. Foster Satyen Kale M. Mohri Karthik Sridharan 152 61 0 30 Dec 2017
Online Learning Without Prior Information Ashok Cutkosky K. Boahen ODL 62 74 0 07 Mar 2017
Online Convex Optimization with Unconstrained Domains and Losses Ashok Cutkosky K. Boahen ODL 78 32 0 07 Mar 2017
On Structured Prediction Theory with Calibrated Convex Surrogate Losses A. Osokin Francis R. Bach Simon Lacoste-Julien 102 61 0 07 Mar 2017
Data-Dependent Stability of Stochastic Gradient Descent Ilja Kuzborskij Christoph H. Lampert MLT 155 166 0 05 Mar 2017
Alternative asymptotics for cointegration tests in large VARs Junhong Lin Lorenzo Rosasco 77 37 0 28 May 2016
Generalization Properties and Implicit Regularization for Multiple Passes SGM Junhong Lin Raffaello Camoriano Lorenzo Rosasco 86 70 0 26 May 2016
MetaGrad: Multiple Learning Rates in Online Learning T. Erven Wouter M. Koolen ODL 138 98 0 29 Apr 2016
Coin Betting and Parameter-Free Online Learning Francesco Orabona D. Pál 208 166 0 12 Feb 2016
Scale-Free Online Learning Francesco Orabona D. Pál 89 104 0 08 Jan 2016
Iterative Regularization for Learning with Convex Loss Functions Junhong Lin Lorenzo Rosasco Ding-Xuan Zhou 102 43 0 31 Mar 2015
Achieving All with No Parameters: Adaptive NormalHedge Haipeng Luo Robert Schapire ODL 83 18 0 20 Feb 2015
M-Power Regularized Least Squares Regression Julien Audiffren Hachem Kadri 50 1 0 09 Oct 2013