Invention Grant
- Patent Title: Regularizing the training of convolutional neural networks
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Application No.: US16422797Application Date: 2019-05-24
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Publication No.: US11409991B2Publication Date: 2022-08-09
- Inventor: Vineet Gupta , Philip M. Long , Hanie Sedghi
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- Agency: Fish & Richardson P.C.
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06N3/08 ; G06F17/16 ; G06F17/14

Abstract:
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a convolutional neural network using a regularization scheme. One of the methods includes repeatedly performing the following operations: obtaining a kernel of a particular convolutional layer; applying a Fourier transform to the kernel; generating a decomposition using singular-value decomposition (SVD); generating a regularized diagonal matrix; generating a recomposition; applying an inverse Fourier transform to the recomposition; and training the convolutional neural network on training inputs.
Public/Granted literature
- US20200372300A1 REGULARIZING THE TRAINING OF CONVOLUTIONAL NEURAL NETWORKS Public/Granted day:2020-11-26
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