- 专利标题: Systems and methods for training neural networks with sparse data
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申请号: US15881632申请日: 2018-01-26
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公开(公告)号: US11244226B2公开(公告)日: 2022-02-08
- 发明人: Carl Jacob Munkberg , Jon Niklas Theodor Hasselgren , Jaakko T. Lehtinen , Timo Oskari Aila
- 申请人: NVIDIA Corporation
- 申请人地址: US CA Santa Clara
- 专利权人: NVIDIA Corporation
- 当前专利权人: NVIDIA Corporation
- 当前专利权人地址: US CA Santa Clara
- 代理机构: Davis Wright Tremaine LLP
- 主分类号: G06N3/08
- IPC分类号: G06N3/08 ; G06N5/04
摘要:
A method, computer readable medium, and system are disclosed for training a neural network model. The method includes the step of selecting an input vector from a set of training data that includes input vectors and sparse target vectors, where each sparse target vector includes target data corresponding to a subset of samples within an output vector of the neural network model. The method also includes the steps of processing the input vector by the neural network model to produce output data for the samples within the output vector and adjusting parameter values of the neural network model to reduce differences between the output vector and the sparse target vector for the subset of the samples.
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