In-Edge AI: Intelligentizing Mobile Edge Computing, Caching and Communication by Federated Learning 搁浅 边缘人工智能:通过联邦学习智能移动边缘计算、缓存和通信 摘要:近年来,随着移动通信技术的快速发展,边缘计算理论和技术越来越受到全球研究人员和工程师的关注,它可以通过网络边缘显著地桥接云的容量和设备的需求,...
In this paper, we investigate an approach to bring edge-AI to end-nodes through a shared machine learning model powered by the blockchain technology and a federated learning framework called iFLBC edge. Our approach addresses the issue of the scarcity of relevant data by devising a mechanism ...
In addition, intermediate memory comprises two parts: the memory footprint required for the activations of each layer ai during the forward pass, and the memory footprint required for the gradients of ai and wi during the backward pass. Note that the same intermediate memory needs to be ...
for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs on any GPU cloud or on-premise cluster. Built on this library, TensorOpera AI (https://TensorOpera.ai) is your generative AI platform at ...
In order to realize the full potential of wireless edge artificial intelligence (AI), very large and diverse datasets will often be required for energy-demanding model training on resource-constrained edge devices. This paper proposes a lead federated ne
Efficient Machine Learning at the Edge in Parallel Abstract: Since the beginning of the digital age, the size and quantity of data sets have grown exponentially because of the proliferation of data captured by mobile devices, vehicles, cameras, microphones, and other internet of things (IoT) devi...
Smart and collaborative industrial IoT: A federated learning and data space approach Industry 4.0 has become a reality by fusing the Industrial Internet of Things(IIoT)and Artificial Intelligence(AI),providing huge opportunities in the way ... B Farahani,AK Monsefi - 数字通信与网络:英文版 被引...
There’s nothing stopping you from combining several different features and signals as the input to your AI algorithms. For example, you could calculate several moving averages of a time series over several different windows and pass them all into a machine learning model together. There are no...
Given the common features of both edge computing and federated learning, edge computing is a naturally suitable environment to apply federated learning framework. Therefore, edge federated learning is more and more appealing in both academic research and industry in recent days. Here, we first have ...
Learning with Differential Privacy-Li Zhang 59:39 国际基础科学大会-Swarm of Micro Flying Robots in the Wild-Xin Zhou 54:00 国际基础科学大会-Lensless Imaging: Overview, Opportunities, and Challenges 59:57 国际基础科学大会-Heterogeneous Graph Neural Network-Chuxu Zhang 49:44 国际基础科学大会-AI ...