公开(公告)号：US11373116B2

公开(公告)日：2022-06-28

申请号：US15980496

申请日：2018-05-15

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Jun Xu ,  Yunfeng Shao ,  Xiao Yang ,  Zheng Yan

IPC: G06F16/00 ,  G06N20/00 ,  H04Q3/545 ,  G06K9/62

Abstract: Embodiments of the present invention provide a model parameter fusion method and apparatus, which relate to the field of machine learning and intend to reduce a data transmission amount and implement dynamical adjustment of computing resources during model parameter fusion. The method includes: dividing, by an ith node, a model parameter of the ith node into N blocks, where the ith node is any node of N nodes that participate in a fusion, and 1≤i≤N≤M; receiving, by the ith node, ith model parameter blocks respectively sent by other nodes of the N nodes than the ith node; fusing, by the ith node, an ith model parameter block of the ith node and the ith model parameter blocks respectively sent by the other nodes, so as to obtain the ith general model parameter block; and distributing, by the ith node, the ith general model parameter block to the other nodes of the N nodes.

公开(公告)号：US11308386B2

公开(公告)日：2022-04-19

申请号：US16423750

申请日：2019-05-28

Applicant: Huawei Technologies Co., Ltd.

Inventor： Ming Wang ,  Zheng Yan ,  Xijun Xue

IPC: G06N3/04 ,  G06N3/063 ,  G06N3/08 ,  G06N3/02

Abstract: A signal processing method and apparatus includes determining a first signal F1(t) output by a first neuron, processing the first signal F1(t) using q orders of synapse weight parameters wq(t), wq−1(t), . . . , w1(t) to obtain a second signal F2(t), and inputting the second signal F2(t) to a second neuron, where the second neuron is in a layer immediately subsequent to that of the first neuron.

公开(公告)号：US20190286969A1

公开(公告)日：2019-09-19

申请号：US16423750

申请日：2019-05-28

Applicant: Huawei Technologies Co., Ltd.

Inventor： Ming Wang ,  Zheng Yan ,  Xijun Xue

IPC: G06N3/04 ,  G06N3/08 ,  G06N3/063

Abstract: A signal processing method and apparatus includes determining a first signal F1(t) output by a first neuron, processing the first signal F1(t) using q orders of synapse weight parameters wq(t), wq−1(t), . . . , w1 (t) to obtain a second signal F2(t), and inputting the second signal F2(t) to a second neuron, where the second neuron is a next-layer neuron of the first neuron.