1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2022★ 1 cited
UNIFY: a Unified Policy Designing Framework for Solving Constrained Optimization Problems with Machine Learning
Mattia Silvestri, Allegra De Filippo, Michele Lombardi +1
The interplay between Machine Learning (ML) and Constrained Optimization (CO) has recently been the subject of increasing interest, leading to a new and prolific research area cove…
cs.AI2020
Injecting Domain Knowledge in Neural Networks: a Controlled Experiment on a Constrained Problem
Mattia Silvestri, Michele Lombardi, Michela Milano
Given enough data, Deep Neural Networks (DNNs) are capable of learning complex input-output relations with high accuracy. In several domains, however, data is scarce or expensive t…