5 citations · 14 across the 5 of their papers we have counts for
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cond-mat.dis-nn2024★ 5 cited
Restoring balance: principled under/oversampling of data for optimal classification
Emanuele Loffredo, Mauro Pastore, Simona Cocco +1
Class imbalance in real-world data poses a common bottleneck for machine learning tasks, since achieving good generalization on under-represented examples is often challenging. Mit…
cond-mat.dis-nn2023★ 4 cited
Unlearning regularization for Boltzmann Machines
Enrico Ventura, Simona Cocco, Rémi Monasson +1
Boltzmann Machines (BMs) are graphical models with interconnected binary units, employed for the unsupervised modeling of data distributions. When trained on real data, BMs show th…