70 citations · 348 across the 10 of their papers we have counts for
3 papers · 1 filter
A Surprising Linear Relationship Predicts Test Performance in Deep Networks
Qianli Liao, Brando Miranda, Andrzej Banburski +2
Given two networks with the same training loss on a dataset, when would they have drastically different test losses and errors? Better understanding of this question of generalizat…
Theory IIIb: Generalization in Deep Networks
Tomaso Poggio, Qianli Liao, Brando Miranda +3
A main puzzle of deep neural networks (DNNs) revolves around the apparent absence of "overfitting", defined in this paper as follows: the expected error does not get worse when inc…
Theory of Deep Learning III: explaining the non-overfitting puzzle
Tomaso Poggio, Kenji Kawaguchi, Qianli Liao +5
A main puzzle of deep networks revolves around the absence of overfitting despite large overparametrization and despite the large capacity demonstrated by zero training error on ra…