Decentralized Recommendation Based on Matrix Factorization: A Comparison of Gossip and Federated Learning

Hegedűs, István, Danner, Gábor, Jelasity, Márk: Decentralized Recommendation Based on Matrix Factorization: A Comparison of Gossip and Federated Learning.
In: Machine Learning and Knowledge Discovery in Databases: International Workshops of ECML PKDD 2019, Würzburg, Germany, September 16–20, 2019, Proceedings, Part I. Springer International Publishing, Cham (Svájc), pp. 317-332. (2020) ISBN 9783030438234; 9783030438227

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Item Type: Book Section
Date: 2020
Number: 1167
Number of Pages: 16
Page Range: pp. 317-332
ISBN: 9783030438234; 9783030438227
Publisher: Springer International Publishing
Place of Publication: Cham (Svájc)
Faculty: Faculty of Science and Informatics
Institution: Szegedi Tudományegyetem
MTMT id: 31264620
DOI id: https://doi.org/10.1007/978-3-030-43823-4_27
Related URLs:
Date Deposited: 2020. Apr. 01. 11:56
Last Modified: 2020. Apr. 01. 16:23
URI: http://publicatio.bibl.u-szeged.hu/id/eprint/18455

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