- Patent Title: Systems and methods for training neural networks with sparse data
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Application No.: US15881632Application Date: 2018-01-26
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Publication No.: US11244226B2Publication Date: 2022-02-08
- Inventor: Carl Jacob Munkberg , Jon Niklas Theodor Hasselgren , Jaakko T. Lehtinen , Timo Oskari Aila
- Applicant: NVIDIA Corporation
- Applicant Address: US CA Santa Clara
- Assignee: NVIDIA Corporation
- Current Assignee: NVIDIA Corporation
- Current Assignee Address: US CA Santa Clara
- Agency: Davis Wright Tremaine LLP
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06N5/04

Abstract:
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.
Public/Granted literature
- US20180357537A1 SYSTEMS AND METHODS FOR TRAINING NEURAL NETWORKS WITH SPARSE DATA Public/Granted day:2018-12-13
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