Generalization Error Bounds with Probabilistic Guarantee for SGD in Nonconvex Optimization

19 February 2018

Papers citing "Generalization Error Bounds with Probabilistic Guarantee for SGD in Nonconvex Optimization"

7 / 7 papers shown

Title
Mutual Information Learned Regressor: an Information-theoretic Viewpoint of Training Regression Systems Jirong Yi Q. Zhang Zhengbo Chen Qiaoan Liu Weizhuo Shao Yusen He Yao Wang SSL 28 0 0 23 Nov 2022
On the Algorithmic Stability and Generalization of Adaptive Optimization Methods Han Nguyen Hai Pham Sashank J. Reddi Barnabas Poczos ODL AI4CE 17 2 0 08 Nov 2022
Stability and Generalization for Markov Chain Stochastic Gradient Methods Puyu Wang Yunwen Lei Yiming Ying Ding-Xuan Zhou 24 18 0 16 Sep 2022
Improved Learning Rates for Stochastic Optimization: Two Theoretical Viewpoints Shaojie Li Yong Liu 26 13 0 19 Jul 2021
Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent Yunwen Lei Yiming Ying MLT 35 126 0 15 Jun 2020
Stagewise Training Accelerates Convergence of Testing Error Over SGD Zhuoning Yuan Yan Yan Rong Jin Tianbao Yang 60 11 0 10 Dec 2018
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark W. Schmidt 139 1,201 0 16 Aug 2016