16 citations · 43 across the 13 of their papers we have counts for
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cs.LG2021★ 1 cited
SGDE: Secure Generative Data Exchange for Cross-Silo Federated Learning
Eugenio Lomurno, Alberto Archetti, Lorenzo Cazzella +3
Privacy regulation laws, such as GDPR, impose transparency and security as design pillars for data processing algorithms. In this context, federated learning is one of the most inf…
cs.LG2021★ 6 cited
Neural Weighted A*: Learning Graph Costs and Heuristics with Differentiable Anytime A*
Alberto Archetti, Marco Cannici, Matteo Matteucci
Recently, the trend of incorporating differentiable algorithms into deep learning architectures arose in machine learning research, as the fusion of neural layers and algorithmic l…