METHOD AND APPARATUS FOR GENERATING A NOISE-RESILIENT MACHINE LEARNING MODEL

    公开(公告)号:US20240330685A1

    公开(公告)日:2024-10-03

    申请号:US18742494

    申请日:2024-06-13

    CPC classification number: G06N3/08

    Abstract: The present application relates to a computer-implemented method for an improved technique for optimising the loss function during deep learning. The method includes receiving a training data set comprising a plurality of data items, initialising weights of at least one neural network layer of the ML model, and training, using an iterative process, the at least one neural network layer of the ML model by inputting, into the at least one neural network layer, the plurality of data items, processing the plurality of data items using the at least one neural network layer and the weights, optimising a loss function of the weights by simultaneously minimising a loss value and a loss sharpness using weights that lie in a neighbourhood having a similar low loss value, wherein the neighbourhood is determined by a geometry of a parameter space defined by the weights of the ML model, and updating the weights of the at least one neural network layer using the optimised loss function.

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