Poster "rademacher complexity" Papers

5 papers found

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Block Coordinate Descent for Neural Networks Provably Finds Global Minima

Shunta Akiyama

NEURIPS 2025arXiv:2510.22667
2
citations

Generalizability of Neural Networks Minimizing Empirical Risk Based on Expressive Power

Lijia Yu, Yibo Miao, Yifan Zhu et al.

ICLR 2025
1
citations

Generalization Bound of Gradient Flow through Training Trajectory and Data-dependent Kernel

Yilan Chen, Zhichao Wang, Wei Huang et al.

NEURIPS 2025arXiv:2506.11357
1
citations

Multiclass Loss Geometry Matters for Generalization of Gradient Descent in Separable Classification

Matan Schliserman, Tomer Koren

NEURIPS 2025arXiv:2505.22359

Boosting Adversarial Training via Fisher-Rao Norm-based Regularization

Xiangyu Yin, Wenjie Ruan

CVPR 2024arXiv:2403.17520
13
citations