Stochastic Approximation of Smooth and Strongly Convex Functions: Beyond
the $O(1/T)$ Convergence Rate

Stochastic Approximation of Smooth and Strongly Convex Functions: Beyond the $O(1/T)$ Convergence Rate

27 January 2019

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Papers citing "Stochastic Approximation of Smooth and Strongly Convex Functions: Beyond the $O(1/T)$ Convergence Rate"

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Title
Exploring Local Norms in Exp-concave Statistical Learning Nikita Puchkin Nikita Zhivotovskiy 138 2 0 21 Feb 2023
Adaptivity and Non-stationarity: Problem-dependent Dynamic Regret for Online Convex Optimization Peng Zhao Yu Zhang Lijun Zhang Zhi Zhou 110 50 0 29 Dec 2021
Towards Noise-adaptive, Problem-adaptive (Accelerated) Stochastic Gradient Descent Sharan Vaswani Benjamin Dubois-Taine Reza Babanezhad 98 13 0 21 Oct 2021
Stability and Generalization for Randomized Coordinate Descent Puyu Wang Liang Wu Yunwen Lei 58 7 0 17 Aug 2021
Improved Learning Rates for Stochastic Optimization: Two Theoretical Viewpoints Shaojie Li Yong Liu 103 13 0 19 Jul 2021
Learning Under Delayed Feedback: Implicitly Adapting to Gradient Delays R. Aviv Ido Hakimi Assaf Schuster Kfir Y. Levy 49 9 0 23 Jun 2021
An Even More Optimal Stochastic Optimization Algorithm: Minibatching and Interpolation Learning Blake E. Woodworth Nathan Srebro 62 22 0 04 Jun 2021
Stability and Deviation Optimal Risk Bounds with Convergence Rate $O(1/n)$ Yegor Klochkov Nikita Zhivotovskiy 81 62 0 22 Mar 2021
Towards Optimal Problem Dependent Generalization Error Bounds in Statistical Learning Theory Yunbei Xu A. Zeevi 116 17 0 12 Nov 2020
Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent Yunwen Lei Yiming Ying MLT 99 129 0 15 Jun 2020
Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence Nicolas Loizou Sharan Vaswani I. Laradji Simon Lacoste-Julien 105 188 0 24 Feb 2020
Memorized Sparse Backpropagation Zhiyuan Zhang Pengcheng Yang Xuancheng Ren Qi Su Xu Sun 83 13 0 24 May 2019