Rethinking Bias-Variance Trade-off for Generalization of Neural Networks

26 February 2020

Papers citing "Rethinking Bias-Variance Trade-off for Generalization of Neural Networks"

31 / 31 papers shown

Title
On the Relationship Between Double Descent of CNNs and Shape/Texture Bias Under Learning Process Shun Iwase Shuya Takahashi Nakamasa Inoue Rio Yokota Ryo Nakamura Hirokatsu Kataoka 74 0 0 04 Mar 2025
Multi-view Structural Convolution Network for Domain-Invariant Point Cloud Recognition of Autonomous Vehicles Younggun Kim Beomsik Cho Seonghoon Ryoo Soomok Lee 3DPC 99 0 0 27 Jan 2025
Understanding Model Ensemble in Transferable Adversarial Attack Wei Yao Zeliang Zhang Huayi Tang Yong Liu 33 2 0 09 Oct 2024
Understanding Optimal Feature Transfer via a Fine-Grained Bias-Variance Analysis Yufan Li Subhabrata Sen Ben Adlam MLT 43 1 0 18 Apr 2024
Rethinking Semi-Supervised Imbalanced Node Classification from Bias-Variance Decomposition Divin Yan Gengchen Wei Chen Yang Shengzhong Zhang Zengfeng Huang AI4CE 38 11 0 28 Oct 2023
Gibbs-Based Information Criteria and the Over-Parameterized Regime Haobo Chen Yuheng Bu Greg Wornell 21 1 0 08 Jun 2023
Double Descent of Discrepancy: A Task-, Data-, and Model-Agnostic Phenomenon Yi-Xiao Luo Bin Dong 26 0 0 25 May 2023
Understanding Difficulty-based Sample Weighting with a Universal Difficulty Measure Xiaoling Zhou Ou Wu Weiyao Zhu Ziyang Liang 27 2 0 12 Jan 2023
A Unified Theory of Diversity in Ensemble Learning Danny Wood Tingting Mu Andrew M. Webb Henry W. J. Reeve M. Luján Gavin Brown UQCV 18 41 0 10 Jan 2023
Task Discovery: Finding the Tasks that Neural Networks Generalize on Andrei Atanov Andrei Filatov Teresa Yeo Ajay Sohmshetty Amir Zamir OOD 40 10 0 01 Dec 2022
Understanding the double descent curve in Machine Learning Luis Sa-Couto J. M. Ramos Miguel Almeida Andreas Wichert 16 1 0 18 Nov 2022
Deep Double Descent via Smooth Interpolation Matteo Gamba Erik Englesson Marten Bjorkman Hossein Azizpour 56 10 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
Sparse Double Descent: Where Network Pruning Aggravates Overfitting Zhengqi He Zeke Xie Quanzhi Zhu Zengchang Qin 69 27 0 17 Jun 2022
Regularization-wise double descent: Why it occurs and how to eliminate it Fatih Yilmaz Reinhard Heckel 25 11 0 03 Jun 2022
Towards Size-Independent Generalization Bounds for Deep Operator Nets Pulkit Gopalani Sayar Karmakar Dibyakanti Kumar Anirbit Mukherjee AI4CE 24 5 0 23 May 2022
Machine Learning and Deep Learning -- A review for Ecologists Maximilian Pichler F. Hartig 36 124 0 11 Apr 2022
On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features Jinxin Zhou Xiao Li Tian Ding Chong You Qing Qu Zhihui Zhu 22 97 0 02 Mar 2022
Understanding the bias-variance tradeoff of Bregman divergences Ben Adlam Neha Gupta Zelda E. Mariet Jamie Smith UQCV UD 17 6 0 08 Feb 2022
An Analysis on Ensemble Learning optimized Medical Image Classification with Deep Convolutional Neural Networks Dominik Muller Iñaki Soto Rey Frank Kramer 16 56 0 27 Jan 2022
Early Stopping for Deep Image Prior Hengkang Wang Taihui Li Zhong Zhuang Tiancong Chen Hengyue Liang Ju Sun 18 62 0 11 Dec 2021
Multi-scale Feature Learning Dynamics: Insights for Double Descent Mohammad Pezeshki Amartya Mitra Yoshua Bengio Guillaume Lajoie 61 25 0 06 Dec 2021
Label Noise in Adversarial Training: A Novel Perspective to Study Robust Overfitting Chengyu Dong Liyuan Liu Jingbo Shang NoLa AAML 56 18 0 07 Oct 2021
On the Generalization of Models Trained with SGD: Information-Theoretic Bounds and Implications Ziqiao Wang Yongyi Mao FedML MLT 32 22 0 07 Oct 2021
A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning Yehuda Dar Vidya Muthukumar Richard G. Baraniuk 29 71 0 06 Sep 2021
To Smooth or Not? When Label Smoothing Meets Noisy Labels Jiaheng Wei Hangyu Liu Tongliang Liu Gang Niu Masashi Sugiyama Yang Liu NoLa 32 69 0 08 Jun 2021
Understanding Double Descent Requires a Fine-Grained Bias-Variance Decomposition Ben Adlam Jeffrey Pennington UD 29 92 0 04 Nov 2020
Regularizing Neural Networks via Adversarial Model Perturbation Yaowei Zheng Richong Zhang Yongyi Mao AAML 22 95 0 10 Oct 2020
An Investigation of Why Overparameterization Exacerbates Spurious Correlations Shiori Sagawa Aditi Raghunathan Pang Wei Koh Percy Liang 146 370 0 09 May 2020
Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond Fanghui Liu Xiaolin Huang Yudong Chen Johan A. K. Suykens BDL 34 172 0 23 Apr 2020
Double Trouble in Double Descent : Bias and Variance(s) in the Lazy Regime Stéphane dÁscoli Maria Refinetti Giulio Biroli Florent Krzakala 93 152 0 02 Mar 2020