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US 2025/0094824 A1Published application
Federated learning with neural graphical models
AssigneeMicrosoft Technology Licensing, LLC
InventorsHarsh SHRIVASTAVA, Urszula Stefania CHAJEWSKA
Life of this patent
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Abstract
The present disclosure relates to methods and systems that provide a federated learning framework using Neural Graphical Models. The federated learning framework combines the individual distributions learned by each client into a global model while keeping the data of each client private within each client's environment. The methods and systems allow for knowledge sharing among the clients without data sharing.
Claims20
A method, comprising:
- receiving, from a plurality of clients, a plurality of feature dependency graphs, wherein each client provides a feature dependency graph created using data of each client;
- generating, using a merge function, a global dependency graph from the plurality of feature dependency graphs, wherein nodes in the global dependency graph contain an intersection of features of the plurality of feature dependency graphs;
- and
- providing, to the plurality of clients, the global dependency graph.
1 more element
A method, comprising:
- receiving, from a plurality of clients, a plurality of Neural Graphical Models, wherein each Neural Graphical Model is trained locally by a client using a global dependency graph and data of the client;
- training a global Neural Graphical Model using the plurality of Neural Graphical Models and the global dependency graph, wherein the global Neural Graphical Model represents an aggregate distribution over a domain of the data used to train each Neural Graphical Model;
- and
- providing, to the plurality of clients, the global Neural Graphical Model.
1 more element
A device, comprising:
- a memory to store data and instructions;
- and
- a processor operable to communicate with the memory, wherein the processor is operable to:
- generate, using a merge function, a global dependency graph from a plurality of feature dependency graphs received from a plurality of clients, wherein nodes in the global dependency graph contain an intersection of features of the plurality of feature dependency graphs;
- provide, to the plurality of clients, the global dependency graph;
- receive, from the plurality of clients, a plurality of Neural Graphical Models trained locally by a client using data from the client and the global dependency graph;
- train a global Neural Graphical Model using the plurality of Neural Graphical Models and the global dependency graph, wherein the global Neural Graphical Model represents an aggregate distribution over a domain of the data used to train each Neural Graphical Model;
- and
- provide, to the plurality of clients, the global Neural Graphical Model.
6 more elements
Dependencies are inferred from the claim text.