Invention Grant
- Patent Title: Generative adversarial network employed for decentralized and confidential AI training
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Application No.: US16238897Application Date: 2019-01-03
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Publication No.: US11010637B2Publication Date: 2021-05-18
- Inventor: Marco Visentini Scarzanella , Phongtharin Vinayavekhin , Jayakorn Vongkulbhisal
- Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Applicant Address: US NY Armonk
- Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee Address: US NY Armonk
- Agency: Tutunjian & Bitetto, P.C.
- Agent Randall Bluestone
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06N3/08

Abstract:
A computer-implemented method is presented for constructing a trained model for a plurality of edge classifiers in a network having a federated classifier, a generator, and a discriminator. The method includes obtaining edge trained models from the plurality of edge devices, each edge trained model being trained independently with data from private data of each edge, training the generator model and discriminator model by employing the edge trained models and an unlabeled set of data by employing a generative adversarial training procedure, generating data samples by the trained generator model, training the federated classifier with the data samples from the generator model, and deploying the trained model back to the plurality of edge devices.
Public/Granted literature
- US20200218937A1 GENERATIVE ADVERSARIAL NETWORK EMPLOYED FOR DECENTRALIZED AND CONFIDENTIAL AI TRAINING Public/Granted day:2020-07-09
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