GLSVLSI

Federated learning (FL) is a collaborative learning scheme to train deep learning models, where collaborating parties can consolidate their models without sharing local data with other parties, hence preserving data privacy. Nevertheless, when ...

The computational complexity of graph neural networks (GNNs) presents a significant obstacle to their widespread adoption in various applications. As the size of the input graph increases, the number of parameters in GNN models grows rapidly, leading to ...

Advanced sensor networks are anticipated to deliver more innovative and cost-efficient monitoring solutions than conventional ones. Low-power technologies, such as Long-Range Wide-Area Network (LoRaWAN), are being integrated into advanced sensor ...

Deep Neural Networks (DNNs) are increasingly applied in various intelligent applications for enhanced accuracy for in-situ decision-making. Considering the cost and longevity, those intelligent applications usually employ energy harvesting (EH) for ...