May 24, 2021 · On-device training for personalized learning is a challenging research problem. Being able to quickly adapt deep prediction models at the edge ...
On-device training for personalized learning is a challenging research problem. Being able to quickly adapt deep prediction models at the edge is necessary to ...
On-device training for personalized learning is a challenging research problem. Being able to quickly adapt deep prediction models at the edge is necessary ...
This method becomes inefficient in many real-world settings because of its high storage space consumption [2], especially in the case of edge devices [33] . On ...
May 24, 2021 · This paper details the implementation and deployment of a hybrid continual learning strategy (AR1*) on a native Android application for ...
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Jan 5, 2022 · Continual Learning at the Edge: Real-Time Training on Smartphone Devices, by L. Pellegrini et al., ESANN, 2021. Continual Learning in Practice ...
Duration: 1:21:41
Posted: Jun 1, 2021
Posted: Jun 1, 2021
Continual Learning at the Edge: Real-Time Training on Smartphone Devices. L Pellegrini, V Lomonaco, G Graffieti, D Maltoni. 29th European Symposium on ...
Training deep neural networks at the edge on light computational devices, embedded systems and robotic platforms is nowadays very challenging. Continual
The paper "Continual Learning at the Edge: Real-Time Training on Smartphone Devices" has been accepted at ESANN 2021 and can be found here. The paper is ...