Resource-Efficient Federated Hyperdimensional Computing Article Swipe

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Nikita Zeulin , Olga Galinina , Nageen Himayat , Sergey Andreev ·

YOU? · · 2023 · Open Access · · DOI: https://doi.org/10.48550/arxiv.2306.01339

In conventional federated hyperdimensional computing (HDC), training larger models usually results in higher predictive performance but also requires more computational, communication, and energy resources. If the system resources are limited, one may have to sacrifice the predictive performance by reducing the size of the HDC model. The proposed resource-efficient federated hyperdimensional computing (RE-FHDC) framework alleviates such constraints by training multiple smaller independent HDC sub-models and refining the concatenated HDC model using the proposed dropout-inspired procedure. Our numerical comparison demonstrates that the proposed framework achieves a comparable or higher predictive performance while consuming less computational and wireless resources than the baseline federated HDC implementation.

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Computer science Dropout (neural networks) Limited resources Baseline (sea) Resource (disambiguation) Distributed computing Wireless Economic shortage Machine learning Computer network Risk analysis (engineering) Telecommunications Linguistics Philosophy Geology Medicine Oceanography Government (linguistics)

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Type: preprint
Language: en
Landing Page: http://arxiv.org/abs/2306.01339
PDF: https://arxiv.org/pdf/2306.01339
OA Status: green
Cited By: 1
Related Works: 10
OpenAlex ID: https://openalex.org/W4379473909

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OpenAlex ID: https://openalex.org/W4379473909

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DOI: https://doi.org/10.48550/arxiv.2306.01339

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Title: Resource-Efficient Federated Hyperdimensional Computing

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Type: preprint

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Language: en

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Publication year: 2023

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Publication date: 2023-06-02

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Authors: Nikita Zeulin, Olga Galinina, Nageen Himayat, Sergey Andreev

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Landing page: https://arxiv.org/abs/2306.01339

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PDF URL: https://arxiv.org/pdf/2306.01339

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Concepts: Computer science, Dropout (neural networks), Limited resources, Baseline (sea), Resource (disambiguation), Distributed computing, Wireless, Economic shortage, Machine learning, Computer network, Risk analysis (engineering), Telecommunications, Linguistics, Philosophy, Geology, Medicine, Oceanography, Government (linguistics)

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Cited by: 1

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