Leveraging Unlabeled Data to Track Memorization

8 December 2022

Papers citing "Leveraging Unlabeled Data to Track Memorization"

50 / 77 papers shown

Title
Early Stopping Against Label Noise Without Validation Data Suqin Yuan Lei Feng Tongliang Liu NoLa 160 18 0 11 Feb 2025
SELC: Self-Ensemble Label Correction Improves Learning with Noisy Labels Yangdi Lu Wenbo He NoLa 52 39 0 02 May 2022
Leveraging Unlabeled Data to Predict Out-of-Distribution Performance Saurabh Garg Sivaraman Balakrishnan Zachary Chase Lipton Behnam Neyshabur Hanie Sedghi OODD OOD 57 126 0 11 Jan 2022
Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations Jiaheng Wei Zhaowei Zhu Weiran Wang Tongliang Liu Gang Niu Yang Liu NoLa 68 249 0 22 Oct 2021
Assessing the Quality of the Datasets by Identifying Mislabeled Samples Vaibhav Pulastya Gaurav Nuti Yash Kumar Atri Tanmoy Chakraborty NoLa 45 5 0 10 Sep 2021
Memorization in Deep Neural Networks: Does the Loss Function matter? Deep Patel P. Sastry TDI 30 8 0 21 Jul 2021
The Evolution of Out-of-Distribution Robustness Throughout Fine-Tuning Anders Andreassen Yasaman Bahri Behnam Neyshabur Rebecca Roelofs OOD OODD 59 80 0 30 Jun 2021
Deep Learning Through the Lens of Example Difficulty R. Baldock Hartmut Maennel Behnam Neyshabur 67 159 0 17 Jun 2021
RATT: Leveraging Unlabeled Data to Guarantee Generalization Saurabh Garg Sivaraman Balakrishnan J. Zico Kolter Zachary Chase Lipton 39 30 0 01 May 2021
Neural Architecture Search with Random Labels Xuanyang Zhang Pengfei Hou Xinming Zhang Jian Sun 47 53 0 28 Jan 2021
How Does a Neural Network's Architecture Impact Its Robustness to Noisy Labels? Jingling Li Mozhi Zhang Keyulu Xu John P. Dickerson Jimmy Ba OOD NoLa 30 19 0 23 Dec 2020
When is Memorization of Irrelevant Training Data Necessary for High-Accuracy Learning? Gavin Brown Mark Bun Vitaly Feldman Adam D. Smith Kunal Talwar 272 93 0 11 Dec 2020
Robustness of Accuracy Metric and its Inspirations in Learning with Noisy Labels Pengfei Chen Junjie Ye Guangyong Chen Jingwei Zhao Pheng-Ann Heng NoLa 108 34 0 08 Dec 2020
A Survey of Label-noise Representation Learning: Past, Present and Future Bo Han Quanming Yao Tongliang Liu Gang Niu Ivor W. Tsang James T. Kwok Masashi Sugiyama NoLa 36 162 0 09 Nov 2020
A Bayesian Perspective on Training Speed and Model Selection Clare Lyle Lisa Schut Binxin Ru Y. Gal Mark van der Wilk 67 24 0 27 Oct 2020
What is being transferred in transfer learning? Behnam Neyshabur Hanie Sedghi Chiyuan Zhang 59 513 0 26 Aug 2020
What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation Vitaly Feldman Chiyuan Zhang TDI 88 452 0 09 Aug 2020
Learning from Noisy Labels with Deep Neural Networks: A Survey Hwanjun Song Minseok Kim Dongmin Park Yooju Shin Jae-Gil Lee NoLa 82 976 0 16 Jul 2020
Early-Learning Regularization Prevents Memorization of Noisy Labels Sheng Liu Jonathan Niles-Weed N. Razavian C. Fernandez‐Granda NoLa 64 561 0 30 Jun 2020
Normalized Loss Functions for Deep Learning with Noisy Labels Xingjun Ma Hanxun Huang Yisen Wang Simone Romano S. Erfani James Bailey NoLa 43 438 0 24 Jun 2020
What Do Neural Networks Learn When Trained With Random Labels? Hartmut Maennel Ibrahim Alabdulmohsin Ilya O. Tolstikhin R. Baldock Olivier Bousquet Sylvain Gelly Daniel Keysers FedML 127 87 0 18 Jun 2020
Speedy Performance Estimation for Neural Architecture Search Binxin Ru Clare Lyle Lisa Schut M. Fil Mark van der Wilk Y. Gal 55 37 0 08 Jun 2020
Rethink the Connections among Generalization, Memorization and the Spectral Bias of DNNs Xiao Zhang Haoyi Xiong Dongrui Wu 71 12 0 29 Apr 2020
Designing Network Design Spaces Ilija Radosavovic Raj Prateek Kosaraju Ross B. Girshick Kaiming He Piotr Dollár GNN 82 1,672 0 30 Mar 2020
Robust and On-the-fly Dataset Denoising for Image Classification Jiaming Song Lunjia Hu Michael Auli Yann N. Dauphin Tengyu Ma NoLa OOD 34 13 0 24 Mar 2020
Coherent Gradients: An Approach to Understanding Generalization in Gradient Descent-based Optimization S. Chatterjee ODL OOD 81 51 0 25 Feb 2020
The Break-Even Point on Optimization Trajectories of Deep Neural Networks Stanislaw Jastrzebski Maciej Szymczak Stanislav Fort Devansh Arpit Jacek Tabor Kyunghyun Cho Krzysztof J. Geras 61 157 0 21 Feb 2020
Improving Generalization by Controlling Label-Noise Information in Neural Network Weights Hrayr Harutyunyan Kyle Reing Greg Ver Steeg Aram Galstyan NoLa 25 55 0 19 Feb 2020
Learning Not to Learn in the Presence of Noisy Labels Liu Ziyin Blair Chen Ru Wang Paul Pu Liang Ruslan Salakhutdinov Louis-Philippe Morency Masahito Ueda NoLa 44 18 0 16 Feb 2020
Identifying Mislabeled Data using the Area Under the Margin Ranking Geoff Pleiss Tianyi Zhang Ethan R. Elenberg Kilian Q. Weinberger NoLa 59 267 0 28 Jan 2020
Deep Double Descent: Where Bigger Models and More Data Hurt Preetum Nakkiran Gal Kaplun Yamini Bansal Tristan Yang Boaz Barak Ilya Sutskever 97 925 0 04 Dec 2019
The intriguing role of module criticality in the generalization of deep networks Niladri S. Chatterji Behnam Neyshabur Hanie Sedghi 44 51 0 02 Dec 2019
Neural Network Memorization Dissection Jindong Gu Volker Tresp FedML 35 12 0 21 Nov 2019
SELF: Learning to Filter Noisy Labels with Self-Ensembling Philipp Kratzer Marc Toussaint Thi Phuong Nhung Ngo T. Nguyen Jim Mainprice Thomas Brox NoLa 65 314 0 04 Oct 2019
Does Learning Require Memorization? A Short Tale about a Long Tail Vitaly Feldman TDI 113 489 0 12 Jun 2019
On the Inductive Bias of Neural Tangent Kernels A. Bietti Julien Mairal 49 255 0 29 May 2019
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks Mingxing Tan Quoc V. Le 3DV MedIm 81 17,950 0 28 May 2019
Simple Black-box Adversarial Attacks Chuan Guo Jacob R. Gardner Yurong You A. Wilson Kilian Q. Weinberger AAML 48 571 0 17 May 2019
Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels Pengfei Chen B. Liao Guangyong Chen Shengyu Zhang NoLa 43 383 0 13 May 2019
Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent Jaehoon Lee Lechao Xiao S. Schoenholz Yasaman Bahri Roman Novak Jascha Narain Sohl-Dickstein Jeffrey Pennington 122 1,089 0 18 Feb 2019
Are All Layers Created Equal? Chiyuan Zhang Samy Bengio Y. Singer 48 140 0 06 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 108 966 0 24 Jan 2019
Theoretically Principled Trade-off between Robustness and Accuracy Hongyang R. Zhang Yaodong Yu Jiantao Jiao Eric Xing L. Ghaoui Michael I. Jordan 94 2,525 0 24 Jan 2019
Frequency Principle: Fourier Analysis Sheds Light on Deep Neural Networks Zhi-Qin John Xu Yaoyu Zhang Yaoyu Zhang Yan Xiao Zheng Ma 107 509 0 19 Jan 2019
Learning to Learn from Noisy Labeled Data Junnan Li Yongkang Wong Qi Zhao Mohan Kankanhalli NoLa 34 331 0 13 Dec 2018
Disentangling Adversarial Robustness and Generalization David Stutz Matthias Hein Bernt Schiele AAML OOD 230 279 0 03 Dec 2018
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers Zeyuan Allen-Zhu Yuanzhi Li Yingyu Liang MLT 106 769 0 12 Nov 2018
Rademacher Complexity for Adversarially Robust Generalization Dong Yin Kannan Ramchandran Peter L. Bartlett AAML 63 258 0 29 Oct 2018
Gradient Descent Provably Optimizes Over-parameterized Neural Networks S. Du Xiyu Zhai Barnabás Póczós Aarti Singh MLT ODL 130 1,261 0 04 Oct 2018
ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design Ningning Ma Xiangyu Zhang Haitao Zheng Jian Sun 128 4,957 0 30 Jul 2018