Mayhoub et al., 2024 - Google Patents
A review of client selection methods in federated learningMayhoub et al., 2024
- Document ID
- 7738131334911587391
- Author
- Mayhoub S
- M. Shami T
- Publication year
- Publication venue
- Archives of Computational Methods in Engineering
External Links
Snippet
Federated learning (FL) is a promising new technology that allows machine learning (ML) models to be trained locally on edge devices while preserving the privacy of the devices' data. FL, as an emerging technology, still suffers from a bunch of challenges, including the …
- 238000012552 review 0 title abstract description 22
Classifications
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- G06F17/30861—Retrieval from the Internet, e.g. browsers
- G06F17/30864—Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems
- G06F17/30867—Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems with filtering and personalisation
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- G06Q10/00—Administration; Management
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- G06Q30/00—Commerce, e.g. shopping or e-commerce
- G06Q30/02—Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
- G06Q30/0202—Market predictions or demand forecasting
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- G—PHYSICS
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- G—PHYSICS
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- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation, e.g. linear programming, "travelling salesman problem" or "cutting stock problem"
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