Representation Based Complexity Measures for Predicting Generalization in Deep Learning

4 December 2020

Papers citing "Representation Based Complexity Measures for Predicting Generalization in Deep Learning"

10 / 10 papers shown

Title
Pretraining with Random Noise for Fast and Robust Learning without Weight Transport Jeonghwan Cheon Sang Wan Lee Se-Bum Paik OOD 242 1 0 27 May 2024
Input margins can predict generalization too Coenraad Mouton Marthinus W. Theunissen Marelie Hattingh Davel AAML UQCV AI4CE 23 3 0 29 Aug 2023
Fantastic DNN Classifiers and How to Identify them without Data Nathaniel R. Dean D. Sarkar 23 1 0 24 May 2023
A Statistical Model for Predicting Generalization in Few-Shot Classification Yassir Bendou Vincent Gripon Bastien Pasdeloup Lukas Mauch Stefan Uhlich Fabien Cardinaux G. B. Hacene Javier Alonso García 21 2 0 13 Dec 2022
Weight Expansion: A New Perspective on Dropout and Generalization Gao Jin Xinping Yi Pengfei Yang Lijun Zhang S. Schewe Xiaowei Huang 29 5 0 23 Jan 2022
GBK-GNN: Gated Bi-Kernel Graph Neural Networks for Modeling Both Homophily and Heterophily Lun Du Xiaozhou Shi Qiang Fu Xiaojun Ma Hengyu Liu Shi Han Dongmei Zhang 40 105 0 29 Oct 2021
In Search of Probeable Generalization Measures Jonathan Jaegerman Khalil Damouni M. M. Ankaralı Konstantinos N. Plataniotis 32 2 0 23 Oct 2021
Tune it the Right Way: Unsupervised Validation of Domain Adaptation via Soft Neighborhood Density Kuniaki Saito Donghyun Kim Piotr Teterwak Stan Sclaroff Trevor Darrell Kate Saenko 48 52 0 24 Aug 2021
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
Norm-Based Capacity Control in Neural Networks Behnam Neyshabur Ryota Tomioka Nathan Srebro 127 577 0 27 Feb 2015