arXiv Machine Learning June 9, 2026 By Yicheng Li, Weiye Gan, Zuoqiang Shi, Qian Lin

Generalization Error Curves for Analytic Spectral Algorithms under Power-law Decay

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arXiv:2401. 01599v4 Announce Type: replace Abstract: The generalization error curve of certain kernel regression method aims at determining the exact order of generalization error with various source condition, noise level and choice of the regularization parameter rather than the minimax rate.

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arXiv AI

Jun 8

Generalization in Deep Neural Networks: Minimax Rates for Gradient Methods

arXiv:2606. 06772v1 Announce Type: cross Abstract: Understanding the generalization performance of over-parameterized neural networks has become a central topic in deep learning theory.

By Junyu Zhou, Puyu Wang, Yunwen Lei, Marius Kloft, Yiming Ying

arXiv Machine Learning

Jul 30

Minimax-Optimal Generalization Bounds for Smooth Deep Neural Networks Trained by (Stochastic) Gradient Descent

arXiv:2606. 06772v2 Announce Type: replace-cross Abstract: Characterizing the optimization dynamics and statistical performance of over-parameterized deep neural networks (DNNs) remains a central challenge in understanding the remarkable success of deep learning.

By Junyu Zhou, Puyu Wang, Dennis Wagner, Yunwen Lei, Marius Kloft, Yiming Ying

arXiv Machine Learning

Sep 15

Neural Operators for Nonlinear Functionals on RKHS

arXiv:2403.12187v2 Announce Type: replace-cross Abstract: Motivated by the abundance of functional data, such as time series and images, we study the approximation and statistical learning of nonline...

By Tian-Yi Zhou, Namjoon Suh, Guang Cheng, Xiaoming Huo

arXiv Machine Learning

Jun 8

Conflicting Biases at the Edge of Stability: Norm versus Sharpness Regularization

arXiv:2505. 21423v3 Announce Type: replace Abstract: The remarkable generalization properties of overparameterized networks are often attributed to implicit biases, such as norm minimization at small learning rates and low sharpness in the Edge-of-Stability regime.

By Maria Matveev, Vit Fojtik, Hung-Hsu Chou, Gitta Kutyniok, Johannes Maly

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arXiv Statistics ML

6d ago

A Flatness-Generalization Relation in the Teacher-Student Tree-Committee Machine

arXiv:2609.31101v1 Announce Type: cross Abstract: The flatness of the loss landscape at a minimizer is a widely used heuristic for reasoning about neural-network generalization, yet evidence for this...

By Brandon Livio Annesi, Davide Straziota, Enrico Maria Malatesta

arXiv Machine Learning

Sep 21

A Smoothed Discrepancy Principle for Random Feature Methods and Neural Networks

arXiv:2609.21017v1 Announce Type: cross Abstract: We study data-driven early stopping for spectral regularisation methods in the classical non-parametric regression setting. Building on the discrepan...

By Mike Nguyen, Nicole M\"ucke

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