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- e737f187-2ef2-4eea-ae30-90bd3f78bcde name "distribution bias" assertion.
- 2b88a076-caef-461a-9e63-bdc2193091a7 name "generator" assertion.
- 37198ce6-b9b0-4622-aa37-a3bf1c1f50ff name "generator" assertion.
- e4f5f982-52f9-4d59-8038-ca6f36c1e7ee name "program generator" assertion.
- c9079960-c974-4d08-b4fc-a2ee2f8d6c3c name "sharing of generator" assertion.
- 7b693717-c22b-4dd8-a293-12fe049c69de name "SGDE allows training of these generators on edge devices where data is collected, enabling sharing of generators, and helping to create unlimited synthetic samples for new machine learning tasks." assertion.
- 01b906ad-cb6f-4c8c-84dd-434b3aa03af6 name "The SGDE protocol initiates on the edge device, subsequently uploading the trained generator to a central server; clients can then download these generators and create synthetic samples, reducing distribution biases, due to the equal class representation of synthetic data." assertion.
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- b4b18b0a-b329-498b-80c5-b2db1c70bcd1 dateModified "2023-12-04 10:32:43.547452+00:00" assertion.
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- a443bee6-0bb2-43eb-9428-906af2273a19 author mailto:alberto1.archetti@mail.polimi.it assertion.
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