BioRender Template

Semi-Supervised Federated Learning for Evolving Data Streams

Created by

Bernard Cobbinah

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Description:

The framework tackles the challenge of learning from evolving data streams while maintaining data privacy. Key features include collaborative learning across devices, adapting to new data patterns, and a focus on data security.

Updated

April 2024

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BioRender Template FAQs

What does the Semi-Supervised Federated Learning for Evolving Data Streams template show?

Is the Semi-Supervised Federated Learning for Evolving Data Streams template free to use?

Yes, you can customize this template with a free BioRender account (no credit card required). Paid plans unlock additional export formats, higher-resolution downloads, and publication permissions.

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Yes, every element is fully editable. Icons, labels, colors, arrows, shapes and layout can all be changed to match your preferences or needs using BioRender's drag-and-drop editor. You can add or remove elements to fully customize your use case.

Is this template accepted for use in journals, theses, or grant applications?

Yes, BioRender icons and templates meet journal, grant, and copyright standards for publication, and many researchers cite BioRender directly in their figure legends.

How do I cite BioRender if I use this template?

Unlock publication permissions with a paid plan, and include 'Created with BioRender.com' in your figure legend, or cite BioRender directly per your journal's guidelines.

What is Semi-Supervised Federated Learning for Evolving Data Streams used for / who typically uses this template?

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