22 citations · 25 across the 3 of their papers we have counts for
3 papers
Tilting the Odds at the Lottery: the Interplay of Overparameterisation and Curricula in Neural Networks
Stefano Sarao Mannelli, Yaraslau Ivashynka, Andrew Saxe +1
A wide range of empirical and theoretical works have shown that overparameterisation can amplify the performance of neural networks. According to the lottery ticket hypothesis, ove…
Bias-inducing geometries: an exactly solvable data model with fairness implications
Stefano Sarao Mannelli, Federica Gerace, Negar Rostamzadeh +1
Machine learning (ML) may be oblivious to human bias but it is not immune to its perpetuation. Marginalisation and iniquitous group representation are often traceable in the very d…
Probing transfer learning with a model of synthetic correlated datasets
Federica Gerace, Luca Saglietti, Stefano Sarao Mannelli +2
Transfer learning can significantly improve the sample efficiency of neural networks, by exploiting the relatedness between a data-scarce target task and a data-abundant source tas…