Predicting the Generalization Gap in Deep Networks with Margin Distributions

28 September 2018

Papers citing "Predicting the Generalization Gap in Deep Networks with Margin Distributions"

48 / 48 papers shown

Title
Early Stopping Against Label Noise Without Validation Data Suqin Yuan Lei Feng Tongliang Liu NoLa 104 16 0 11 Feb 2025
Multi-Instance Partial-Label Learning with Margin Adjustment Wei Tang Yin-Fang Yang Zhaofei Wang Feiyu Xiong Hao Fei 73 0 0 22 Jan 2025
Understanding Generalization in Quantum Machine Learning with Margins Tak Hur Daniel K. Park AI4CE 34 1 0 11 Nov 2024
Towards Scalable and Versatile Weight Space Learning Konstantin Schurholt Michael W. Mahoney Damian Borth 50 15 0 14 Jun 2024
Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures Paul Viallard Rémi Emonet Amaury Habrard Emilie Morvant Valentina Zantedeschi 39 3 0 19 Feb 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
An extended asymmetric sigmoid with Perceptron (SIGTRON) for imbalanced linear classification Hyenkyun Woo 20 0 0 26 Dec 2023
Input margins can predict generalization too Coenraad Mouton Marthinus W. Theunissen Marelie Hattingh Davel AAML UQCV AI4CE 23 3 0 29 Aug 2023
MarginMatch: Improving Semi-Supervised Learning with Pseudo-Margins Tiberiu Sosea Cornelia Caragea 16 12 0 17 Aug 2023
Deep neural networks architectures from the perspective of manifold learning German Magai AAML AI4CE 24 6 0 06 Jun 2023
Sparsified Model Zoo Twins: Investigating Populations of Sparsified Neural Network Models D. Honegger Konstantin Schurholt Damian Borth 31 4 0 26 Apr 2023
Permutation Equivariant Neural Functionals Allan Zhou Kaien Yang Kaylee Burns Adriano Cardace Yiding Jiang Samuel Sokota J. Zico Kolter Chelsea Finn 35 47 0 27 Feb 2023
On the Relationship Between Explanation and Prediction: A Causal View Amir-Hossein Karimi Krikamol Muandet Simon Kornblith Bernhard Schölkopf Been Kim FAtt CML 37 14 0 13 Dec 2022
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
Instance-Dependent Generalization Bounds via Optimal Transport Songyan Hou Parnian Kassraie Anastasis Kratsios Andreas Krause Jonas Rothfuss 22 6 0 02 Nov 2022
Multi-Object Navigation with dynamically learned neural implicit representations Pierre Marza L. Matignon Olivier Simonin Christian Wolf 35 23 0 11 Oct 2022
Why neural networks find simple solutions: the many regularizers of geometric complexity Benoit Dherin Michael Munn M. Rosca David Barrett 55 31 0 27 Sep 2022
Deep Double Descent via Smooth Interpolation Matteo Gamba Erik Englesson Marten Bjorkman Hossein Azizpour 63 11 0 21 Sep 2022
Membership Inference Attacks and Generalization: A Causal Perspective Teodora Baluta Shiqi Shen S. Hitarth Shruti Tople Prateek Saxena OOD MIACV 40 18 0 18 Sep 2022
Improving Self-supervised Learning for Out-of-distribution Task via Auxiliary Classifier Harshita Boonlia T. Dam Md Meftahul Ferdaus S. Anavatti Ankan Mullick OODD 16 4 0 07 Sep 2022
On the Strong Correlation Between Model Invariance and Generalization Weijian Deng Stephen Gould Liang Zheng OOD 32 16 0 14 Jul 2022
Neural Collapse: A Review on Modelling Principles and Generalization Vignesh Kothapalli 25 74 0 08 Jun 2022
Delving into the Openness of CLIP Shuhuai Ren Lei Li Xuancheng Ren Guangxiang Zhao Xu Sun VLM 25 13 0 04 Jun 2022
Investigating Generalization by Controlling Normalized Margin Alexander R. Farhang Jeremy Bernstein Kushal Tirumala Yang Liu Yisong Yue 31 6 0 08 May 2022
BERTops: Studying BERT Representations under a Topological Lens Jatin Chauhan Manohar Kaul 24 3 0 02 May 2022
CONTINUER: Maintaining Distributed DNN Services During Edge Failures A. Majeed Peter Kilpatrick I. Spence Blesson Varghese 14 0 0 25 Apr 2022
Topology and geometry of data manifold in deep learning German Magai A. Ayzenberg AAML 21 11 0 19 Apr 2022
Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data Yaoqing Yang Ryan Theisen Liam Hodgkinson Joseph E. Gonzalez Kannan Ramchandran Charles H. Martin Michael W. Mahoney 88 17 0 06 Feb 2022
Label-Free Model Evaluation with Semi-Structured Dataset Representations Xiaoxiao Sun Yunzhong Hou Hongdong Li Liang Zheng 13 11 0 01 Dec 2021
Hyper-Representations: Self-Supervised Representation Learning on Neural Network Weights for Model Characteristic Prediction Konstantin Schurholt Dimche Kostadinov Damian Borth SSL 29 14 0 28 Oct 2021
In Search of Probeable Generalization Measures Jonathan Jaegerman Khalil Damouni M. M. Ankaralı Konstantinos N. Plataniotis 24 2 0 23 Oct 2021
Graphs as Tools to Improve Deep Learning Methods Carlos Lassance Myriam Bontonou Mounia Hamidouche Bastien Pasdeloup Lucas Drumetz Vincent Gripon GNN AI4CE AAML 47 0 0 08 Oct 2021
Exploring the Limits of Large Scale Pre-training Samira Abnar Mostafa Dehghani Behnam Neyshabur Hanie Sedghi AI4CE 60 114 0 05 Oct 2021
Predicting with Confidence on Unseen Distributions Devin Guillory Vaishaal Shankar Sayna Ebrahimi Trevor Darrell Ludwig Schmidt UQCV OOD 20 116 0 07 Jul 2021
Deep Learning Through the Lens of Example Difficulty R. Baldock Hartmut Maennel Behnam Neyshabur 47 156 0 17 Jun 2021
What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments? Weijian Deng Stephen Gould Liang Zheng 39 62 0 10 Jun 2021
Generalization bounds via distillation Daniel J. Hsu Ziwei Ji Matus Telgarsky Lan Wang FedML 17 32 0 12 Apr 2021
NeurIPS 2020 Competition: Predicting Generalization in Deep Learning Yiding Jiang Pierre Foret Scott Yak Daniel M. Roy H. Mobahi Gintare Karolina Dziugaite Samy Bengio Suriya Gunasekar Isabelle M Guyon Behnam Neyshabur Google Research OOD 24 55 0 14 Dec 2020
Predicting Generalization in Deep Learning via Local Measures of Distortion Abhejit Rajagopal Vamshi C. Madala S. Chandrasekaran P. Larson 8 1 0 13 Dec 2020
Semantically Robust Unpaired Image Translation for Data with Unmatched Semantics Statistics Zhiwei Jia Bodi Yuan Kangkang Wang Hong Wu David Clifford Zhiqiang Yuan Hao Su VLM 44 21 0 09 Dec 2020
Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial Robustness Guillermo Ortiz-Jiménez Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 29 48 0 19 Oct 2020
Analysis of Generalizability of Deep Neural Networks Based on the Complexity of Decision Boundary Shuyue Guan Murray H. Loew 27 25 0 16 Sep 2020
An Investigation of the Weight Space to Monitor the Training Progress of Neural Networks Konstantin Schurholt Damian Borth 29 3 0 18 Jun 2020
Directional convergence and alignment in deep learning Ziwei Ji Matus Telgarsky 17 163 0 11 Jun 2020
Predicting Neural Network Accuracy from Weights Thomas Unterthiner Daniel Keysers Sylvain Gelly Olivier Bousquet Ilya O. Tolstikhin 30 101 0 26 Feb 2020
Understanding the Decision Boundary of Deep Neural Networks: An Empirical Study David Mickisch F. Assion Florens Greßner W. Günther M. Motta AAML 19 34 0 05 Feb 2020
Information-Theoretic Local Minima Characterization and Regularization Zhiwei Jia Hao Su 27 19 0 19 Nov 2019
Improved Sample Complexities for Deep Networks and Robust Classification via an All-Layer Margin Colin Wei Tengyu Ma AAML OOD 36 85 0 09 Oct 2019