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Enhancing Once-For-All: A Study on Parallel Blocks, Skip Connections and Early Exits
The use of Neural Architecture Search (NAS) techniques to automate the design of neural networks has become increasingly popular in recent years.
POPNASv3: a Pareto-Optimal Neural Architecture Search Solution for Image and Time Series Classification
The automated machine learning (AutoML) field has become increasingly relevant in recent years.
POPNASv2: An Efficient Multi-Objective Neural Architecture Search Technique
With its sequential model-based optimization strategy, Progressive Neural Architecture Search (PNAS) represents a possible step forward to face this resources issue.
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