On Generalization Error Bounds of Noisy Gradient Methods for Non-Convex Learning

2 February 2019

Papers citing "On Generalization Error Bounds of Noisy Gradient Methods for Non-Convex Learning"

27 / 27 papers shown

Title
NeuralGrok: Accelerate Grokking by Neural Gradient Transformation Xinyu Zhou Simin Fan Martin Jaggi Jie Fu 41 0 0 24 Apr 2025
Randomized Pairwise Learning with Adaptive Sampling: A PAC-Bayes Analysis Sijia Zhou Yunwen Lei Ata Kabán 34 0 0 03 Apr 2025
Stability-based Generalization Bounds for Variational Inference Yadi Wei R. Khardon BDL 49 0 0 17 Feb 2025
Understanding the Generalization Error of Markov algorithms through Poissonization Benjamin Dupuis Maxime Haddouche George Deligiannidis Umut Simsekli 49 0 0 11 Feb 2025
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
When Foresight Pruning Meets Zeroth-Order Optimization: Efficient Federated Learning for Low-Memory Devices Peng Zhang Yingjie Liu Yingbo Zhou Xiao Du Xian Wei Ting Wang Mingsong Chen FedML 32 1 0 08 May 2024
Uniform Generalization Bounds on Data-Dependent Hypothesis Sets via PAC-Bayesian Theory on Random Sets Benjamin Dupuis Paul Viallard George Deligiannidis Umut Simsekli 48 2 0 26 Apr 2024
Leveraging Gradients for Unsupervised Accuracy Estimation under Distribution Shift Renchunzi Xie Ambroise Odonnat Vasilii Feofanov I. Redko Jianfeng Zhang Bo An UQCV 80 1 0 17 Jan 2024
Information-Theoretic Generalization Bounds for Transductive Learning and its Applications Huayi Tang Yong Liu 62 1 0 08 Nov 2023
Generalization Bounds for Label Noise Stochastic Gradient Descent Jung Eun Huh Patrick Rebeschini 13 1 0 01 Nov 2023
Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient Descent Lingjiong Zhu Mert Gurbuzbalaban Anant Raj Umut Simsekli 34 6 0 20 May 2023
Machine Learning and the Future of Bayesian Computation Steven Winter Trevor Campbell Lizhen Lin Sanvesh Srivastava David B. Dunson TPM 47 4 0 21 Apr 2023
Does Federated Learning Really Need Backpropagation? H. Feng Tianyu Pang Chao Du Wei Chen Shuicheng Yan Min Lin FedML 36 10 0 28 Jan 2023
Limitations of Information-Theoretic Generalization Bounds for Gradient Descent Methods in Stochastic Convex Optimization Mahdi Haghifam Borja Rodríguez Gálvez Ragnar Thobaben Mikael Skoglund Daniel M. Roy Gintare Karolina Dziugaite 31 17 0 27 Dec 2022
Exploring the Algorithm-Dependent Generalization of AUPRC Optimization with List Stability Peisong Wen Qianqian Xu Zhiyong Yang Yuan He Qingming Huang 53 10 0 27 Sep 2022
Beyond Lipschitz: Sharp Generalization and Excess Risk Bounds for Full-Batch GD Konstantinos E. Nikolakakis Farzin Haddadpour Amin Karbasi Dionysios S. Kalogerias 43 17 0 26 Apr 2022
Sharper Utility Bounds for Differentially Private Models Yilin Kang Yong Liu Jian Li Weiping Wang FedML 35 3 0 22 Apr 2022
Stability Based Generalization Bounds for Exponential Family Langevin Dynamics A. Banerjee Tiancong Chen Xinyan Li Yingxue Zhou 34 8 0 09 Jan 2022
Stochastic Anderson Mixing for Nonconvex Stochastic Optimization Fu Wei Chenglong Bao Yang Liu 30 19 0 04 Oct 2021
Generalization Bounds For Meta-Learning: An Information-Theoretic Analysis Qi Chen Changjian Shui M. Marchand 40 43 0 29 Sep 2021
Improved Learning Rates for Stochastic Optimization: Two Theoretical Viewpoints Shaojie Li Yong Liu 26 13 0 19 Jul 2021
Stability of SGD: Tightness Analysis and Improved Bounds Yikai Zhang Wenjia Zhang Sammy Bald Vamsi Pingali Chao Chen Mayank Goswami MLT 27 36 0 10 Feb 2021
Shape Matters: Understanding the Implicit Bias of the Noise Covariance Jeff Z. HaoChen Colin Wei J. Lee Tengyu Ma 32 94 0 15 Jun 2020
Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent Yunwen Lei Yiming Ying MLT 35 126 0 15 Jun 2020
Sharpened Generalization Bounds based on Conditional Mutual Information and an Application to Noisy, Iterative Algorithms Mahdi Haghifam Jeffrey Negrea Ashish Khisti Daniel M. Roy Gintare Karolina Dziugaite 34 105 0 27 Apr 2020
Information-Theoretic Generalization Bounds for SGLD via Data-Dependent Estimates Jeffrey Negrea Mahdi Haghifam Gintare Karolina Dziugaite Ashish Khisti Daniel M. Roy FedML 115 147 0 06 Nov 2019
Norm-Based Capacity Control in Neural Networks Behnam Neyshabur Ryota Tomioka Nathan Srebro 127 577 0 27 Feb 2015