MULTI-TASK GATING FOR MACHINE LEARNING SYSTEMS

    公开(公告)号:US20250094781A1

    公开(公告)日:2025-03-20

    申请号:US18468873

    申请日:2023-09-18

    Abstract: Systems and techniques are described herein for training and using multitask machine learning models. For example, a computing device can obtain training data for a first task in a layer in a neural network; perform, based on a determination from a first gating mechanism, the shared function on shared features of the training data using at least one shared channel to generate a shared feature map; perform, based on the determination from the first gating mechanism, the first task-specific function on first task-specific features of the training data using at least one first task-specific channel to generate a first task-specific feature map; generate an output for the first task-specific branch based on performing the shared function on the shared features and performing the first task-specific function on the first task-specific features; and update at least one parameter of the first gating mechanism based on the output.

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