公开(公告)号：US20200342358A1

公开(公告)日：2020-10-29

申请号：US16956258

申请日：2017-12-22

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Adrian FLANAGAN ,  Kuan Eeik TAN ,  Qiang FU ,  Yevgeniy IVANCHENKO

IPC: G06N20/00 ,  G06N5/04 ,  H04L29/08 ,  H04L29/06

Abstract: A client including a processor and a memory having computer readable instructions stored thereon that, when executed by the processor, cause the client to connect to a server utilizing a global set of items and at least one model. The client is also caused to utilize at least one model downloaded from said server. The client is additionally caused to generate a recommendation set, including at least one of said items based on said at least one of said downloaded models and a local client data set stored on said client. The recommendation set includes a personalized item recommendation for a user of said client.

公开(公告)号：US20240220347A1

公开(公告)日：2024-07-04

申请号：US18606002

申请日：2024-03-15

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Zhaojiao HAN ,  Xinteng ZHAO ,  Xianjun HE ,  Qiang FU

IPC: G06F11/07

CPC classification number: G06F11/0772

Abstract: A network interface card, a message sending method, and a storage apparatus are provided. The network interface card includes a processor and a communication interface connected to the processor. The processor is configured to obtain a first piece of first indication information and a first piece of second indication information. The first piece of first indication information indicates a first identifier of a non-volatile storage medium corresponding to a first RDMA message, and the first piece of second indication information indicates whether the non-volatile storage medium corresponding to the first identifier is faulty. The communication interface is configured to send the first RDMA message when the first piece of first indication information and the first piece of second indication information indicate that the non-volatile storage medium corresponding to the first RDMA message is not faulty.

公开(公告)号：US20220012601A1

公开(公告)日：2022-01-13

申请号：US17484886

申请日：2021-09-24

Applicant: Huawei Technologies Co., Ltd.

Inventor： Muhammad AMAD-UD-DIN ,  Adrian FLANAGAN ,  Kuan Eeik TAN ,  Elena IVANNIKOVA ,  Qiang FU

IPC: G06N5/02 ,  G06N5/00

Abstract: A Federated learning server and a method are provided. The Federated learning server is configured to aggregate a plurality of received model updates to update a master machine learning model. Once a pre-defined threshold or interval for received model updates is reached, a set of current hyper-parameter values and corresponding validation set performance metrics obtained from the updated master machine learning model are sent to a hyper-parameter optimization model. The optimization model infers the next set of optimal hyper-parameters using pairwise history of hyper-parameter values and the corresponding performance metrics. The inferred hyper-parameter values are sent to the Federated Learning server which updates the master machine learning model with the updated set of hyper-parameter values and redistributes the updated master machine learning model with the updated set of hyper-parameter values. According to the application, hyper-parameter optimization in a Federated learning mode can be realized to provide accurate personalized recommendations.