271 citations · 597 across the 16 of their papers we have counts for
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An Analytical Theory of Auxiliary Learning
Federico Milanesio, Alessandro Ingrosso, Matteo Osella
Auxiliary learning is an optimization paradigm in which a neural network's performance on a target task is improved by jointly training it on additional tasks. However, the mechani…
The Advantage of Fine-Grained Training
Davide Pirovano, Federico Milanesio, Michele Caselle +2
In classification problems, models are trained to predict a class label based on the input data features. However, class labels are organized hierarchically in many datasets. While…
Inversion dynamics of class manifolds in deep learning reveals tradeoffs underlying generalisation
Simone Ciceri, Lorenzo Cassani, Matteo Osella +3
To achieve near-zero training error in a classification problem, the layers of a feed-forward network have to disentangle the manifolds of data points with different labels, to fac…