Making Hard Problems Easier with Custom Data Distributions and Loss Regularization: A Case Study in Modular Arithmetic

Fuente: arXiv

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Bibliographic Details
Main Authors:	Saxena, Eshika, Alfarano, Alberto, Charton, François, Allen-Zhu, Zeyuan, Wenger, Emily, Lauter, Kristin
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
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Internet

https://arxiv.org/abs/2410.03569