The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
May. 03, 2022

Filed:

Feb. 15, 2017
Applicant:

Samsung Electronics Co., Ltd., Gyeonggi-do, KR;

Inventors:

Yoo Jin Choi, San Diego, CA (US);

Mostafa El-Khamy, San Diego, CA (US);

Jungwon Lee, San Diego, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06N 3/08 (2006.01); G06N 3/063 (2006.01); G06F 17/16 (2006.01);
U.S. Cl.
CPC ...
G06N 3/08 (2013.01); G06F 17/16 (2013.01); G06N 3/063 (2013.01); G06N 3/082 (2013.01); G06N 3/084 (2013.01);
Abstract

Apparatuses and methods of manufacturing same, systems, and methods for performing network parameter quantization in deep neural networks are described. In one aspect, diagonals of a second-order partial derivative matrix (a Hessian matrix) of a loss function of network parameters of a neural network are determined and then used to weight (Hessian-weighting) the network parameters as part of quantizing the network parameters. In another aspect, the neural network is trained using first and second moment estimates of gradients of the network parameters and then the second moment estimates are used to weight the network parameters as part of quantizing the network parameters. In yet another aspect, network parameter quantization is performed by using an entropy-constrained scalar quantization (ECSQ) iterative algorithm. In yet another aspect, network parameter quantization is performed by quantizing the network parameters of all layers of a deep neural network together at once.


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