Federated Learning

Three Common Model Aggregation Methods in Federated Learning (FL) with TensorFlow Examples

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Three Common Model Aggregation Methods in Federated Learning (FL) with TensorFlow Examples

Source：DeepHub IMBA This article is approximately 1200 words, recommended reading for 7 minutes Federated Learning (FL) is an excellent ML method that enables multiple devices (such as Internet of Things (IoT) devices) or computers to collaborate in model training without sharing their data. The “clients” are the computers and devices used in FL, which can … Read more

Understanding Transformers and Federated Learning

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Understanding Transformers and Federated Learning

The Transformer, as an attention-based encoder-decoder architecture, has not only revolutionized the field of Natural Language Processing (NLP) but has also made groundbreaking contributions in the field of Computer Vision (CV). Compared to Convolutional Neural Networks (CNNs), Vision Transformers (ViT) rely on excellent modeling capabilities, achieving outstanding performance on multiple benchmarks such as ImageNet, COCO, … Read more