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Federated Learning - Opportunities and Application Challenges

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Advances in Computational Collective Intelligence (ICCCI 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1864))

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Abstract

In this paper our intention was to present a brief literature review focused on the latest research of the Federated Learning paradigm in order to identify current research trends, possible future directions of development, and challenges in this area. Federated learning as a new, powerful distributed intelligent paradigm can take on various forms in order to fit a diverse set of problems in a wide range of domains, economy, finance, medicine, agriculture and other industrial sectors. Based on presented research results, several key opportunities for future work can be identified and some emerging are connected to communication costs and performance of federated models trained by different algorithms.

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Authors and Affiliations

  1. University of Novi Sad, Faculty of Sciences, Novi Sad, Serbia

    Mihailo Ilić & Mirjana Ivanović

Authors
  1. Mihailo Ilić
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  2. Mirjana Ivanović
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Corresponding authors

Correspondence to Mihailo Ilić or Mirjana Ivanović .

Editor information

Editors and Affiliations

  1. Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Eötvös Loránd University, Budapest, Hungary

    János Botzheim

  3. Eötvös Loránd University, Budapest, Hungary

    László Gulyás

  4. Universidad Complutense de Madrid, Madrid, Spain

    Manuel Nunez

  5. Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

    Jan Treur

  6. University of Münster, Münster, Germany

    Gottfried Vossen

  7. Wrocław University of Science and Technology, Wrocław, Poland

    Adrianna Kozierkiewicz

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Ilić, M., Ivanović, M. (2023). Federated Learning - Opportunities and Application Challenges. In: Nguyen, N.T., et al. Advances in Computational Collective Intelligence. ICCCI 2023. Communications in Computer and Information Science, vol 1864. Springer, Cham. https://doi.org/10.1007/978-3-031-41774-0_38

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  • DOI: https://doi.org/10.1007/978-3-031-41774-0_38

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-41773-3

  • Online ISBN: 978-3-031-41774-0

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