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cond-mat.dis-nn2019
Scaling description of generalization with number of parameters in deep learning
Mario Geiger, Arthur Jacot, Stefano Spigler +6
Supervised deep learning involves the training of neural networks with a large number of parameters. For large enough , in the so-called over-parametrized regime, one can es…
cond-mat.dis-nn2018
The jamming transition as a paradigm to understand the loss landscape of deep neural networks
Mario Geiger, Stefano Spigler, Stéphane d'Ascoli +4
Deep learning has been immensely successful at a variety of tasks, ranging from classification to AI. Learning corresponds to fitting training data, which is implemented by descend…