Cover Image

Understanding Robust Overfitting from the Feature Generalization Perspective

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yu, Chaojian, Shi, Xiaolong, Yu, Jun, Han, Bo, Liu, Tongliang
Format:	Preprint
Published:	2023
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

On the Over-Memorization During Natural, Robust and Catastrophic Overfitting
by: Lin, Runqi, et al.
Published: (2023)

Layer-Aware Analysis of Catastrophic Overfitting: Revealing the Pseudo-Robust Shortcut Dependency
by: Lin, Runqi, et al.
Published: (2024)

Eliminating Catastrophic Overfitting Via Abnormal Adversarial Examples Regularization
by: Lin, Runqi, et al.
Published: (2024)

MeGU: Machine-Guided Unlearning with Target Feature Disentanglement
by: Wang, Haoyu, et al.
Published: (2026)

Rethinking Deep Research from the Perspective of Web Content Distribution Matching
by: Yu, Zixuan, et al.
Published: (2026)

Generative Model Inversion Through the Lens of the Manifold Hypothesis
by: Peng, Xiong, et al.
Published: (2025)

BadLabel: A Robust Perspective on Evaluating and Enhancing Label-noise Learning
by: Zhang, Jingfeng, et al.
Published: (2023)

Stealthy and Adjustable Text-Guided Backdoor Attacks on Multimodal Pretrained Models
by: Zhang, Yiyang, et al.
Published: (2026)

Robust Training of Federated Models with Extremely Label Deficiency
by: Zhang, Yonggang, et al.
Published: (2024)

Understanding Generalization in Transformers: Error Bounds and Training Dynamics Under Benign and Harmful Overfitting
by: Zhang, Yingying, et al.
Published: (2025)

Mitigating Label Noise on Graph via Topological Sample Selection
by: Wu, Yuhao, et al.
Published: (2024)

Overfitting in Adaptive Robust Optimization
by: Zhu, Karl, et al.
Published: (2025)

Mitigating Structural Overfitting: A Distribution-Aware Rectification Framework for Missing Feature Imputation
by: Song, Yifan, et al.
Published: (2025)

Enhancing Sample Selection Against Label Noise by Cutting Mislabeled Easy Examples
by: Yuan, Suqin, et al.
Published: (2025)

Tackling Noisy Labels with Network Parameter Additive Decomposition
by: Wang, Jingyi, et al.
Published: (2024)

How to Mitigate Overfitting in Weak-to-strong Generalization?
by: Shi, Junhao, et al.
Published: (2025)

A Survey of Weight Space Learning: Understanding, Representation, and Generation
by: Han, Xiaolong, et al.
Published: (2026)

Provable Robust Overfitting Mitigation in Wasserstein Distributionally Robust Optimization
by: Liu, Shuang, et al.
Published: (2025)

The Surprising Harmfulness of Benign Overfitting for Adversarial Robustness
by: Hao, Yifan, et al.
Published: (2024)

Model Inversion Attacks: A Survey of Approaches and Countermeasures
by: Zhou, Zhanke, et al.
Published: (2024)

Theoretical Analysis of Robust Overfitting for Wide DNNs: An NTK Approach
by: Fu, Shaopeng, et al.
Published: (2023)

Instance-dependent Early Stopping
by: Yuan, Suqin, et al.
Published: (2025)

Testing for Overfitting
by: Schmidt, James
Published: (2023)

What If the Input is Expanded in OOD Detection?
by: Zhang, Boxuan, et al.
Published: (2024)

On the Clean Generalization and Robust Overfitting in Adversarial Training from Two Theoretical Views: Representation Complexity and Training Dynamics
by: Li, Binghui, et al.
Published: (2023)

Residual Stream Analysis of Overfitting And Structural Disruptions
by: Liu, Quan, et al.
Published: (2026)

Relative Overfitting and Accept-Reject Framework
by: Liu, Yanxin, et al.
Published: (2025)

2-in-1 Accelerator: Enabling Random Precision Switch for Winning Both Adversarial Robustness and Efficiency
by: Fu, Yonggan, et al.
Published: (2021)

Neural auto-designer for enhanced quantum kernels
by: Lei, Cong, et al.
Published: (2024)

Provable Weak-to-Strong Generalization via Benign Overfitting
by: Wu, David X., et al.
Published: (2024)

Benign Overfitting in Out-of-Distribution Generalization of Linear Models
by: Tang, Shange, et al.
Published: (2024)

Envisioning Outlier Exposure by Large Language Models for Out-of-Distribution Detection
by: Cao, Chentao, et al.
Published: (2024)

Adjusted Overfitting Regression
by: Wilson, Dylan
Published: (2024)

Overfitting In Contrastive Learning?
by: Rabin, Zachary, et al.
Published: (2024)

Understanding Private Learning From Feature Perspective
by: Ding, Meng, et al.
Published: (2025)

SubFlow: Sub-mode Conditioned Flow Matching for Diverse One-Step Generation
by: Lin, Yexiong, et al.
Published: (2026)

Fairness Overfitting in Machine Learning: An Information-Theoretic Perspective
by: Laakom, Firas, et al.
Published: (2025)

Understanding Adversarial Robustness from Feature Maps of Convolutional Layers
by: Xu, Cong, et al.
Published: (2022)

Mitigating Overfitting in Graph Neural Networks via Feature and Hyperplane Perturbation
by: Choi, Yoonhyuk, et al.
Published: (2022)

Overfitting and Generalizing with (PAC) Bayesian Prediction in Noisy Binary Classification
by: Zhu, Xiaohan, et al.
Published: (2026)