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cs.LG2022
How deep convolutional neural networks lose spatial information with training
Umberto M. Tomasini, Leonardo Petrini, Francesco Cagnetta +1
A central question of machine learning is how deep nets manage to learn tasks in high dimensions. An appealing hypothesis is that they achieve this feat by building a representatio…
stat.ML2022★ 6 cited
Learning sparse features can lead to overfitting in neural networks
Leonardo Petrini, Francesco Cagnetta, Eric Vanden-Eijnden +1
It is widely believed that the success of deep networks lies in their ability to learn a meaningful representation of the features of the data. Yet, understanding when and how this…