Müller K, Bodendorf F (2023)
Publication Language: English
Publication Type: Conference contribution, Conference Contribution
Publication year: 2023
Publisher: AHFE Open Access
Conference Proceedings Title: The Human Side of Service Engineering. AHFE (2023) International Conference.
DOI: 10.54941/ahfe1003126
Open Access Link: https://openaccess.cms-conferences.org/publications/book/978-1-958651-84-1/article/978-1-958651-84-1_25
The performance and generalizability of AI-based enterprise applications depends on the quantity, quality, and diversity of training data. However, data usually exi- sts in the form of data silos at individual sites. With cross-silo federated learning knowledge extracted from data silos that are distributed across multiple enterpri- ses can be combined to improve the predictive performance of AI models without sharing and centralizing potentially sensitive raw data. The decentralized learning approach thus offers new privacy-preserving opportunities for cross-company colla- boration, knowledge management, and the development of intelligent applications and services in federated enterprise networks. Since federated learning enables collaboration between both cooperating and competing companies, this literature review of application-based papers analyzes the differences in the design and stra- tegic management of federated enterprise networks as a function of the actors’ relationships.
APA:
Müller, K., & Bodendorf, F. (2023). Cross-silo federated learning in enterprise networks with cooperative and competing actors. In Christine Leitner, Jens Neuhüttler, Clara Bassano and Debra Satterfield (Eds.), The Human Side of Service Engineering. AHFE (2023) International Conference.. San Francisco, US: AHFE Open Access.
MLA:
Müller, Kristina, and Freimut Bodendorf. "Cross-silo federated learning in enterprise networks with cooperative and competing actors." Proceedings of the 14th International Conference on Applied Human Factors and Ergonomics (AHFE 2023) and the Affiliated Conferences, San Francisco Ed. Christine Leitner, Jens Neuhüttler, Clara Bassano and Debra Satterfield, AHFE Open Access, 2023.
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