177 citations · 551 across the 17 of their papers we have counts for
4 papers · 1 filter
Playing the Lottery With Concave Regularizers for Sparse Trainable Neural Networks
Giulia Fracastoro, Sophie M. Fosson, Andrea Migliorati +1
The design of sparse neural networks, i.e., of networks with a reduced number of parameters, has been attracting increasing research attention in the last few years. The use of spa…
RAN-GNNs: breaking the capacity limits of graph neural networks
Diego Valsesia, Giulia Fracastoro, Enrico Magli
Graph neural networks have become a staple in problems addressing learning and analysis of data defined over graphs. However, several results suggest an inherent difficulty in extr…
Survival and Neural Models for Private Equity Exit Prediction
Giuseppe C. Calafiore, Marisa H. Morales, Vittorio Tiozzo +2
Within the Private Equity (PE) market, the event of a private company undertaking an Initial Public Offering (IPO) is usually a very high-return one for the investors in the compan…
Sparse and Center Classifiers
Giuseppe C. Calafiore, Giulia Fracastoro
The nearest-centroid classifier is a simple linear-time classifier based on computing the centroids of the data classes in the training phase, and then assigning a new datum to the…