Stability and Convergence Trade-off of Iterative Optimization Algorithms

4 April 2018

Papers citing "Stability and Convergence Trade-off of Iterative Optimization Algorithms"

26 / 26 papers shown

Title
Understanding Generalization of Federated Learning: the Trade-off between Model Stability and Optimization Dun Zeng Zheshun Wu Shiyu Liu Yu Pan Xiaoying Tang Zenglin Xu MLT FedML 89 1 0 25 Nov 2024
Uniformly Stable Algorithms for Adversarial Training and Beyond Jiancong Xiao Jiawei Zhang Zhimin Luo Asuman Ozdaglar AAML 48 0 0 03 May 2024
Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization Liang Zhang Junchi Yang Amin Karbasi Niao He 34 2 0 26 Oct 2023
Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient Descent Lingjiong Zhu Mert Gurbuzbalaban Anant Raj Umut Simsekli 39 6 0 20 May 2023
Cyclic and Randomized Stepsizes Invoke Heavier Tails in SGD than Constant Stepsize Mert Gurbuzbalaban Yuanhan Hu Umut Simsekli Lingjiong Zhu LRM 28 1 0 10 Feb 2023
On the Algorithmic Stability and Generalization of Adaptive Optimization Methods Han Nguyen Hai Pham Sashank J. Reddi Barnabas Poczos ODL AI4CE 27 2 0 08 Nov 2022
Stability Analysis and Generalization Bounds of Adversarial Training Jiancong Xiao Yanbo Fan Ruoyu Sun Jue Wang Zhimin Luo AAML 38 30 0 03 Oct 2022
Exploring the Algorithm-Dependent Generalization of AUPRC Optimization with List Stability Peisong Wen Qianqian Xu Zhiyong Yang Yuan He Qingming Huang 58 10 0 27 Sep 2022
Uniform Stability for First-Order Empirical Risk Minimization Amit Attia Tomer Koren 25 5 0 17 Jul 2022
Algorithmic Stability of Heavy-Tailed Stochastic Gradient Descent on Least Squares Anant Raj Melih Barsbey Mert Gurbuzbalaban Lingjiong Zhu Umut Simsekli 24 9 0 02 Jun 2022
Stability vs Implicit Bias of Gradient Methods on Separable Data and Beyond Matan Schliserman Tomer Koren 24 23 0 27 Feb 2022
Benefit of Interpolation in Nearest Neighbor Algorithms Yue Xing Qifan Song Guang Cheng 22 28 0 23 Feb 2022
On the Generalization of Models Trained with SGD: Information-Theoretic Bounds and Implications Ziqiao Wang Yongyi Mao FedML MLT 39 22 0 07 Oct 2021
Improved Learning Rates for Stochastic Optimization: Two Theoretical Viewpoints Shaojie Li Yong Liu 26 13 0 19 Jul 2021
From inexact optimization to learning via gradient concentration Bernhard Stankewitz Nicole Mücke Lorenzo Rosasco 31 5 0 09 Jun 2021
Stability of SGD: Tightness Analysis and Improved Bounds Yikai Zhang Wenjia Zhang Sammy Bald Vamsi Pingali Chao Chen Mayank Goswami MLT 27 37 0 10 Feb 2021
Federated Accelerated Stochastic Gradient Descent Honglin Yuan Tengyu Ma FedML 30 172 0 16 Jun 2020
Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent Yunwen Lei Yiming Ying MLT 43 126 0 15 Jun 2020
Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses Raef Bassily Vitaly Feldman Cristóbal Guzmán Kunal Talwar MLT 24 192 0 12 Jun 2020
Implicit Regularization of Accelerated Methods in Hilbert Spaces Nicolò Pagliana Lorenzo Rosasco 26 18 0 30 May 2019
High probability generalization bounds for uniformly stable algorithms with nearly optimal rate Vitaly Feldman J. Vondrák 35 154 0 27 Feb 2019
An Empirical Study of Large-Batch Stochastic Gradient Descent with Structured Covariance Noise Yeming Wen Kevin Luk Maxime Gazeau Guodong Zhang Harris Chan Jimmy Ba ODL 25 22 0 21 Feb 2019
Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks Sanjeev Arora S. Du Wei Hu Zhiyuan Li Ruosong Wang MLT 57 961 0 24 Jan 2019
Veridical Data Science Bin Yu Karl Kumbier 23 162 0 23 Jan 2019
Gradient Descent Finds Global Minima of Deep Neural Networks S. Du Jason D. Lee Haochuan Li Liwei Wang Masayoshi Tomizuka ODL 44 1,126 0 09 Nov 2018
On the Generalization of Stochastic Gradient Descent with Momentum Ali Ramezani-Kebrya Kimon Antonakopoulos V. Cevher Ashish Khisti Ben Liang MLT 19 24 0 12 Sep 2018