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cs.LG2022
PARTIME: Scalable and Parallel Processing Over Time with Deep Neural Networks
Enrico Meloni, Lapo Faggi, Simone Marullo +4
In this paper, we present PARTIME, a software library written in Python and based on PyTorch, designed specifically to speed up neural networks whenever data is continuously stream…
cs.LG2021
Friendly Training: Neural Networks Can Adapt Data To Make Learning Easier
Simone Marullo, Matteo Tiezzi, Marco Gori +1
In the last decade, motivated by the success of Deep Learning, the scientific community proposed several approaches to make the learning procedure of Neural Networks more effective…
cs.LG2020
Developing Constrained Neural Units Over Time
Alessandro Betti, Marco Gori, Simone Marullo +1
In this paper we present a foundational study on a constrained method that defines learning problems with Neural Networks in the context of the principle of least cognitive action,…