# The Geometric Occam's Razor Implicit in Deep Learning

@inproceedings{Dherin2021TheGO, title={The Geometric Occam's Razor Implicit in Deep Learning}, author={Benoit Richard Umbert Dherin and Micheal Munn and David G. T. Barrett}, year={2021} }

In over-parameterized deep neural networks there can be many possible parameter configurations that fit the training data exactly. However, the properties of these interpolating solutions are poorly understood. We argue that over-parameterized neural networks trained with stochastic gradient descent are subject to a Geometric Occam’s Razor; that is, these networks are implicitly regularized by the geometric model complexity. For one-dimensional regression, the geometric model complexity is…

## One Citation

Manifold Characteristics That Predict Downstream Task Performance

- Computer Science
- 2022

It is shown that self-supervised methods learn an RM where alterations lead to large but constant size changes, indicating a smoother RM than fully supervised methods.

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