DECENTRALIZED FEDERATED LEARNING SYSTEM
A participant node of a distributed ledger network may identify a distributed federated learning (DFL) smart contract stored on a blockchain. The DFL smart contract may include an aggregation sequence. The aggregation sequence may include an ordered sequence of participant node identifiers. The part...
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| creator | Le, Anh-Dung Giordano, Giuseppe Pasic, Haris Schiatti, Luca |
| description | A participant node of a distributed ledger network may identify a distributed federated learning (DFL) smart contract stored on a blockchain. The DFL smart contract may include an aggregation sequence. The aggregation sequence may include an ordered sequence of participant node identifiers. The participant node may generate a trained model by training a global model with training data. The participant node may detect, on the blockchain, a first transition token indicative of a first model previously aggregated by another participant node. The participant node may receive the first model. The participant node may aggregate the first model with the trained model to generate a second model. The participant node may store, on the blockchain, a second transition token indicative of the second model. A successor node identified in the aggregation sequence may further aggregate the second model with an additional model in response to detection of the second transition token. |
| format | Patent |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC COMMUNICATION TECHNIQUE ELECTRIC DIGITAL DATA PROCESSING ELECTRICITY PHYSICS TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION |
| title | DECENTRALIZED FEDERATED LEARNING SYSTEM |
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