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cs.LG2025
The Dynamics of Generalization in Deep Learning
Rubing Yang, Pratik Chaudhari
We derive a differential equation that governs the evolution of the generalization gap when a model is trained by gradient descent-based methods. This differential equation is driv…
cs.LG2023
The Training Process of Many Deep Networks Explores the Same Low-Dimensional Manifold
Jialin Mao, Itay Griniasty, Han Kheng Teoh +5
We develop information-geometric techniques to analyze the trajectories of the predictions of deep networks during training. By examining the underlying high-dimensional probabilis…