With the rapid evolution of Internet of Things (IoT) and artificial intelligence (AI), the industry 4.0 era has arisen. As per the IBM prediction, by the constant spread of 5G technology, the IoT intend to be more extensively utilized in industries. Recently, federated learning (FL) turned ...
Our federated learning framework brings intelligence to every device, enabling secure, scalable AI from the cloud to the edge, all while keeping your data safe.
参与期刊:AI, Applied Sciences, Computers, Electronics, IoT, ASI, Sensors具体信息如下: Dear Colleagues, In the context of 6G networks and advanced edge AI (artificial intelligence) applications, Federated Edge Intelligence (FEI) is rapidly becoming a key technology for realizing distributed, scalable,...
orchestrate and sustain the network infrastructure ranging from topology management (edge site orchestration), to data and service provisioning. Among such techniques,AIandMachine Learning(ML) are considered as a key solution for many challenges. The marriage ofedge computingand AI established a new re...
GDPR, HIPAA, EU AI Act, and country specific regulations Care vs AI Data is collected for patient care, not for use in machine learning research Interoperability Different systems have different labels and structures Incomplete Heterogeneous, missing data, lacks medical context ...
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One vision of a future artificial intelligence (AI) is where many separate units can learn independently over a lifetime and share their knowledge with each other. The synergy between lifelong learning and sharing has the potential to create a society of AI systems, as each individual unit can...
In this chapter, we study semi-supervised edge learning, where the model is first initialized via resource-efficient FL across many edge devices and then personalized for an edge device with limited data samples. In particular, we delve into adaptive device selection and scheduling problem for ...
Wang X, Han Y, Leung VC et al (2020) Edge AI: convergence of edge computing and artificial intelligence, 1st edn. Springer, Singapore Book Google Scholar Zhao Y, Hryniewicki MK (2018) XGBOD: improving supervised outlier detection with unsupervised representation learning. In: International join...
Edge AI Edge computing Artificial intelligence Fog computing Machine learning Cloud computing 1. Introduction As IT developed after 2000, Cloud Computing was established as a novel computing infrastructure for the Internet based on highly resourced data centres. Interest in and adoption of cloud computing...