Invention Grant
- Patent Title: Methods and arrangements to quantize a neural network with machine learning
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Application No.: US16009456Application Date: 2018-06-15
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Publication No.: US11216719B2Publication Date: 2022-01-04
- Inventor: Somdeb Majumdar , Ron Banner , Marcel Nassar , Lior Storfer , Adnan Agbaria , Evren Tumer , Tristan Webb , Xin Wang
- Applicant: INTEL CORPORATION
- Applicant Address: US CA Santa Clara
- Assignee: INTEL CORPORATION
- Current Assignee: INTEL CORPORATION
- Current Assignee Address: US CA Santa Clara
- Agency: Kacvinsky Daisak Bluni PLLC
- Main IPC: G06N3/04
- IPC: G06N3/04 ; G06N3/08 ; G06N3/063

Abstract:
Logic may quantize a primary neural network. Logic may generate, by a secondary neural network logic circuitry for a primary neural network logic circuitry, quantization parameters. The primary neural network logic circuitry may comprise a primary neural network with multiple layers trainable with an objective function. Each of the multiple layers of the primary neural network may comprise multiple tensors. The secondary neural network logic circuitry may comprise one or more secondary neural networks trainable with the objective function to output the quantization parameters to the tensors.
Public/Granted literature
- US20190042945A1 METHODS AND ARRANGEMENTS TO QUANTIZE A NEURAL NETWORK WITH MACHINE LEARNING Public/Granted day:2019-02-07
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