AUTOMATICALLY AND EFFICIENTLY GENERATING SEARCH SPACES FOR NEURAL NETWORK

    公开(公告)号:WO2022265573A2

    公开(公告)日:2022-12-22

    申请号:PCT/SG2022/050343

    申请日:2022-05-23

    Applicant: LEMON INC.

    Abstract: A super-network comprising a plurality of layers may be generated. Each layer may comprise cells with different structures. A predetermined number of cells from each layer may be selected. A plurality of cells may be generated based on selected cells using a local mutation model, wherein the local mutation model comprises a mutation window for removing redundant edges from each selected cell. Performance of the plurality of cells may be evaluated using a differentiable fitness scoring function. The operations of the generating a plurality of cells using the local mutation model, the evaluating performance of the plurality of cells using the differentiable fitness scoring function and the selecting the subset of cells based on the evaluation results may be iteratively performed until the super-network converges. A search space for each layer may be generated based on a predetermined top number of cells with largest fitness scores after the super-network converges.

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