公开(公告)号：US20230089380A1

公开(公告)日：2023-03-23

申请号：US17993430

申请日：2022-11-23

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Chenhan JIANG ,  Hang XU ,  Zhenguo LI ,  Xiaodan LIANG

IPC: G06N3/04

Abstract: A neural network construction method and apparatus in the field of artificial intelligence, to accurately and efficiently construct a target neural network. The constructed target neural network has high output accuracy, may be further applied to different application scenarios, and has a strong generalization capability. The method includes: obtaining a start point network, where the start point network includes a plurality of serial subnets; performing at least one time of transformation on the start point network based on a preset first search space to obtain a serial network, where the first search space includes a range of parameters used for transforming the start point network; and if the serial network meets a preset condition, training the serial network by using a preset dataset to obtain a trained serial network; and if the trained serial network meets a termination condition, obtaining a target neural network based on the trained serial network.

公开(公告)号：US20240070436A1

公开(公告)日：2024-02-29

申请号：US17900592

申请日：2022-08-31

Applicant: Huawei Technologies Co., Ltd.

Inventor： Hang XU ,  Lu HOU ,  Guansong LU ,  Minzhe NIU ,  Zhenguo LI ,  Runhui HUANG ,  Lewei YAO ,  Chunjing XU ,  Xiaodan LIANG

IPC: G06N3/04 ,  G06F40/284

CPC classification number: G06N3/0454 ,  G06F40/284

Abstract: A method is provided for data processing performed by a processing system. The method comprises determining a set of first tokens for first data and a set of second token for second data, each token comprising information associated with a segment of the respective data, determining pair-wise similarities between the set of first tokens and the set of second tokens, each pair comprising a first token in the set of first tokens and a second token in the set of second tokens, determining, for each first token in the set of first tokens, a maximum similarity based on the determined pair-wise similarities between the respective first token and the second tokens in the set of second tokens, and determining a first similarity between the first data and the second data by aggregating the maximum similarities corresponding to the first tokens in the set of first set of tokens.