6 citations · 7 across the 3 of their papers we have counts for
3 papers
cs.LG2022★ 6 cited
POPNASv2: An Efficient Multi-Objective Neural Architecture Search Technique
Andrea Falanti, Eugenio Lomurno, Stefano Samele +2
Automating the research for the best neural network model is a task that has gained more and more relevance in the last few years. In this context, Neural Architecture Search (NAS)…
cs.LG2022★ 1 cited
On the utility and protection of optimization with differential privacy and classic regularization techniques
Eugenio Lomurno, Matteo matteucci
Nowadays, owners and developers of deep learning models must consider stringent privacy-preservation rules of their training data, usually crowd-sourced and retaining sensitive inf…
cs.CV2021
Improving Multi-View Stereo via Super-Resolution
Eugenio Lomurno, Andrea Romanoni, Matteo Matteucci
Today, Multi-View Stereo techniques are able to reconstruct robust and detailed 3D models, especially when starting from high-resolution images. However, there are cases in which t…