The predominant paradigm for using machine learning models on a device is to train a
model in the cloud and perform inference using the trained model on the device. However …

Model predictive control (MPC) has become one of the well-established modern control
methods for three-phase inverters with an output LC filter, where a high-quality voltage with …

Artificial intelligence (AI) research and market have grown rapidly in the last few years, and
this trend is expected to continue with many potential advancements and innovations in this …

Federated learning (FL) has attracted more and more attention recently. The integration of
FL and edge computing makes the edge system more efficient and intelligent. FL usually …

Deep neural networks with large model sizes achieve state-of-the-art results for tasks in
computer vision and natural language processing. However, such models are too compute …

The emergence of the Internet of Things (IoT) has led to a remarkable increase in the
volume of data generated at the network edge. In order to support real-time smart IoT …

Artificial intelligence (AI) research and market have grown rapidly in the last few years and
this trend is expected to continue with many potential advancements and innovations in this …

As computer architectures continue to integrate application-specific hardware, it is critical to
understand the relative performance of devices for maximum app acceleration. The goal of …

Deep neural networks with large model sizes achieve state-of-the-art results for tasks in
computer vision (CV) and natural language processing (NLP). However, these large-scale …

Withthe rapiddevelopment of deep learning, the size of data sets anddeepneuralnetworks
(DNNs) models are also booming. As a result, the intolerable long time for models' training …