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Federated Learning (FL) stands at the intersection of privacy preservation and decentralized data use, revolutionizing practical machine learning. This approach maintains data on local devices, contributing to collective learning, and addresses increasing concerns about data privacy and security.
Feb 13, 2024
Federated learning - Nature
www.nature.com › scientific reports
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Scholarly articles for Federated Learning

scholar.google.com › citations
A review of applications in federated learning
Li · Cited by 989
Federated learning: Opportunities and challenges
Mammen · Cited by 226
A survey on federated learning
Zhang · Cited by 1116

Federated Learning: A Paradigm Shift in Data Privacy and Model Training

medium.com › federated-learning-a-para...
Federated Learning from medium.com
Mar 1, 2024 · At its core, Federated Learning is a collaborative machine learning technique that trains an algorithm across multiple devices or servers with local data ...

A Survey on Efficient Federated Learning Methods for Foundation ...

arxiv.org › cs
Jan 9, 2024 · Abstract:Federated Learning (FL) has become an established technique to facilitate privacy-preserving collaborative training across a multitude of clients.

What is Federated Learning - YouTube

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Video for Federated Learning
Duration: 8:01
Posted: May 30, 2024

IBM Federated Learning - Docs | IBM Cloud Pak for Data as a Service

dataplatform.cloud.ibm.com › fed-lea
Jul 15, 2024 · Federated Learning provides the tools for multiple remote parties to collaboratively train a single machine learning model without sharing data.
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Federated learning is not a cure-all for data ethics - Nature

www.nature.com › ... › comment
Mar 18, 2024 · The term 'federated' refers to the fact that learning is performed by a federation of participating clients. Essentially, a model 'travels' to multiple ...

The Power of Federated Learning with Synthetic Data - Medium

medium.com › intel-tech › the-power-of-...
Nov 2, 2023 · Federated learning works by allowing many collaborators to train models based on their local data, then periodically aggregating local model parameters to build ...
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Speed Up Federated Learning in Heterogeneous Environment - arXiv

arxiv.org › cs
Dec 9, 2023 · Abstract:Federated learning (FL) enables collaboratively training a model while keeping the training data decentralized and private.

Recent methodological advances in federated learning for healthcare

www.sciencedirect.com › article › pii
Jun 14, 2024 · Federated learning adds significant methodological complexity to conventional centralized machine learning, requiring distributed optimization, communication ...