Federated Learning

Federated Learning - Federated learning is an approach to machine learning that addresses data governance and privacy concerns by enabling the collaborative training of algorithms without transferring data to a central location. In this model, each device trains on data locally and shares its local model parameters instead of sharing the training data, and different federated learning systems have various topologies for parameter sharing.

Class Information

Identification

Label (rdfs)
Federated Learning
Preferred Label
None
Alternative Labels
Collaborative AI Training, Decentralized Learning, Distributed Machine Learning, Privacy-Preserving Learning
Identifier
N/A

Definition and Examples

Definition
Federated learning is an approach to machine learning that addresses data governance and privacy concerns by enabling the collaborative training of algorithms without transferring data to a central location. In this model, each device trains on data locally and shares its local model parameters instead of sharing the training data, and different federated learning systems have various topologies for parameter sharing.
Examples
  • N/A

Translations

N/A

Class Relationships

Parent Class Of
  • N/A
Is Defined By
N/A
See Also
N/A

Additional Information

Comment
N/A
Description
N/A
Notes
  • N/A
Deprecated
False

Metadata

History Note
N/A
Editorial Note
N/A
In Scheme
N/A
Source
N/A
Country
N/A

Graph