6 citations · 19 across the 16 of their papers we have counts for
3 papers · 1 filter
POPNASv3: a Pareto-Optimal Neural Architecture Search Solution for Image and Time Series Classification
Andrea Falanti, Eugenio Lomurno, Danilo Ardagna +1
The automated machine learning (AutoML) field has become increasingly relevant in recent years. These algorithms can develop models without the need for expert knowledge, facilitat…
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)…
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…