Federated Learning

Limitations and Solutions of Federated Learning Privacy Protection in the AI Era

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Limitations and Solutions of Federated Learning Privacy Protection in the AI Era

Limitations and Solutions of Federated Learning Privacy Protection in the AI Era Liu Zegang (Associate Professor, Southwest University of Political Science and Law) [Abstract] Legislation on artificial intelligence (AI) often tends to favor specific technologies. Federated learning is a mainstream machine learning technology whose greatest advantage lies in its architecture design that fully considers privacy … Read more

Training BERT and ResNet on Smartphones: 35% Energy Reduction

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Training BERT and ResNet on Smartphones: 35% Energy Reduction

Researchers state that they see edge training as an optimization problem, thereby discovering the optimal scheduling to achieve minimal energy consumption under a given memory budget. Currently, deep learning models are widely deployed on edge devices such as smartphones and embedded platforms for inference. Training, however, is still primarily conducted on large cloud servers equipped … Read more

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