June 21, 2024, 4:49 a.m. | Samiul Alam, Tuo Zhang, Tiantian Feng, Hui Shen, Zhichao Cao, Dong Zhao, JeongGil Ko, Kiran Somasundaram, Shrikanth S. Narayanan, Salman Avestimehr, M

cs.LG updates on arXiv.org arxiv.org

arXiv:2310.00109v2 Announce Type: replace
Abstract: There is a significant relevance of federated learning (FL) in the realm of Artificial Intelligence of Things (AIoT). However, most existing FL works do not use datasets collected from authentic IoT devices and thus do not capture unique modalities and inherent challenges of IoT data. To fill this critical gap, in this work, we introduce FedAIoT, an FL benchmark for AIoT. FedAIoT includes eight datasets collected from a wide range of IoT devices. These datasets …

artificial artificial intelligence arxiv benchmark cs.dc cs.dl cs.lg federated learning intelligence replace things type

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