6 citations · 7 across the 3 of their papers we have counts for
3 papers · 1 filter
Enhancing Once-For-All: A Study on Parallel Blocks, Skip Connections and Early Exits
Simone Sarti, Eugenio Lomurno, Andrea Falanti +1
The use of Neural Architecture Search (NAS) techniques to automate the design of neural networks has become increasingly popular in recent years. The proliferation of devices with…
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)…