Normalized Flat Minima: Exploring Scale Invariant Definition of Flat Minima for Neural Networks using PAC-Bayesian Analysis

15 January 2019

Papers citing "Normalized Flat Minima: Exploring Scale Invariant Definition of Flat Minima for Neural Networks using PAC-Bayesian Analysis"

24 / 24 papers shown

Title
The Uncanny Valley: Exploring Adversarial Robustness from a Flatness Perspective Nils Philipp Walter Linara Adilova Jilles Vreeken Michael Kamp AAML 51 2 0 27 May 2024
Evolutionary algorithms as an alternative to backpropagation for supervised training of Biophysical Neural Networks and Neural ODEs James Hazelden Yuhan Helena Liu Eli Shlizerman E. Shea-Brown 49 2 0 17 Nov 2023
How to escape sharp minima with random perturbations Kwangjun Ahn Ali Jadbabaie S. Sra ODL 34 6 0 25 May 2023
Rethinking Model Ensemble in Transfer-based Adversarial Attacks Huanran Chen Yichi Zhang Yinpeng Dong Xiao Yang Hang Su Junyi Zhu AAML 33 56 0 16 Mar 2023
The Geometry of Neural Nets' Parameter Spaces Under Reparametrization Agustinus Kristiadi Felix Dangel Philipp Hennig 32 11 0 14 Feb 2023
A Modern Look at the Relationship between Sharpness and Generalization Maksym Andriushchenko Francesco Croce Maximilian Müller Matthias Hein Nicolas Flammarion 3DH 19 56 0 14 Feb 2023
Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel Sungyub Kim Si-hun Park Kyungsu Kim Eunho Yang BDL 32 4 0 30 Sep 2022
Understanding the Generalization Benefit of Normalization Layers: Sharpness Reduction Kaifeng Lyu Zhiyuan Li Sanjeev Arora FAtt 47 71 0 14 Jun 2022
Attack-Agnostic Adversarial Detection Jiaxin Cheng Mohamed Hussein J. Billa Wael AbdAlmageed AAML 28 0 0 01 Jun 2022
PACTran: PAC-Bayesian Metrics for Estimating the Transferability of Pretrained Models to Classification Tasks Nan Ding Xi Chen Tomer Levinboim Soravit Changpinyo Radu Soricut 35 26 0 10 Mar 2022
On PAC-Bayesian reconstruction guarantees for VAEs Badr-Eddine Chérief-Abdellatif Yuyang Shi Arnaud Doucet Benjamin Guedj DRL 53 17 0 23 Feb 2022
Anticorrelated Noise Injection for Improved Generalization Antonio Orvieto Hans Kersting F. Proske Francis R. Bach Aurelien Lucchi 76 44 0 06 Feb 2022
When Do Flat Minima Optimizers Work? Jean Kaddour Linqing Liu Ricardo M. A. Silva Matt J. Kusner ODL 28 58 0 01 Feb 2022
On the Power-Law Hessian Spectrums in Deep Learning Zeke Xie Qian-Yuan Tang Yunfeng Cai Mingming Sun P. Li ODL 42 9 0 31 Jan 2022
Exponential escape efficiency of SGD from sharp minima in non-stationary regime Hikaru Ibayashi Masaaki Imaizumi 34 4 0 07 Nov 2021
User-friendly introduction to PAC-Bayes bounds Pierre Alquier FedML 64 199 0 21 Oct 2021
Minimum sharpness: Scale-invariant parameter-robustness of neural networks Hikaru Ibayashi Takuo Hamaguchi Masaaki Imaizumi 25 5 0 23 Jun 2021
ASAM: Adaptive Sharpness-Aware Minimization for Scale-Invariant Learning of Deep Neural Networks Jungmin Kwon Jeongseop Kim Hyunseong Park I. Choi 48 282 0 23 Feb 2021
A Random Matrix Theory Approach to Damping in Deep Learning Diego Granziol Nicholas P. Baskerville AI4CE ODL 29 2 0 15 Nov 2020
Learning Rates as a Function of Batch Size: A Random Matrix Theory Approach to Neural Network Training Diego Granziol S. Zohren Stephen J. Roberts ODL 37 49 0 16 Jun 2020
A Diffusion Theory For Deep Learning Dynamics: Stochastic Gradient Descent Exponentially Favors Flat Minima Zeke Xie Issei Sato Masashi Sugiyama ODL 28 17 0 10 Feb 2020
Hessian based analysis of SGD for Deep Nets: Dynamics and Generalization Xinyan Li Qilong Gu Yingxue Zhou Tiancong Chen A. Banerjee ODL 42 51 0 24 Jul 2019
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 310 2,896 0 15 Sep 2016
Pac-Bayesian Supervised Classification: The Thermodynamics of Statistical Learning O. Catoni 164 454 0 03 Dec 2007