CPC G06N 20/00 (2019.01) | 20 Claims |
1. A system of decentralized machine learning (ML) comprising:
a self-healing computer node of a blockchain network comprising a plurality of computer nodes, the self-healing computer node when recovering from a fault condition within the blockchain network being programmed to:
determine, by the self-healing computer node, that the self-healing computer node is unable to share training parameters in a first iteration of training a machine-learning model;
based on the determination, generate a first blockchain transaction comprising an indication that the self-healing computer node is out-of-sync with the first iteration of training the machine-learned model, wherein the first blockchain transaction is to be added to a distributed ledger and informs the plurality of computer nodes that the self-healing computer node is not ready to participate in a second iteration of training the machine-learned model;
obtain a global ML state from the distributed ledger;
compare the obtained global ML state with a local ML state at the self-healing computer node to determine whether the local ML state is consistent with the global ML state;
based on the comparing, determine that the global ML state is not consistent with the local ML state;
in response to the determining recover the local ML state using a trigger of a corrective action;
determine, by the self-healing computer node, that the self-healing computer node is able to share the training parameters in the second iteration of training the machine-learning model;
based on the determination, generate a second blockchain transaction comprising an indication that the self-healing computer node is in-sync with the second iteration of training the machine-learned model, wherein the second blockchain transaction is to be added to the distributed ledger and informs the plurality of computer nodes that the self-healing computer node is ready to participate in the second iteration of training the machine-learned model; and
re-enroll the self-healing computer node with the blockchain network to participate in the second iteration of training the machine-learned model.
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