公开(公告)号：US20230206024A1

公开(公告)日：2023-06-29

申请号：US17891617

申请日：2022-08-19

Applicant: Beijing Baidu Netcom Science Technology Co., Ltd.

Inventor： Ji Liu ,  Zhihua Wu ,  Danlei Feng ,  Chendi Zhou ,  Minxu Zhang ,  Xinxuan Wu ,  Xuefeng Yao ,  Dejing Dou ,  Dianhai Yu ,  Yanjun Ma

IPC: G06N3/04 ,  G06F11/34

CPC classification number: G06N3/04 ,  G06F11/3409

Abstract: A resource allocation method, including: determining a neural network model to be allocated resources, and determining a set of devices capable of providing resources for the neural network model; determining, based on the set of devices and the neural network model, first set of evaluation points including first number of evaluation points, each of which corresponds to one resource allocation scheme and resource use cost corresponding to the resource allocation scheme; updating and iterating first set of evaluation points to obtain second set of evaluation points including second number of evaluation points, each of which corresponds to one resource allocation scheme and resource use cost corresponding to the resource allocation scheme, and second number being greater than first number; and selecting a resource allocation scheme with minimum resource use cost from the second set of evaluation points as a resource allocation scheme for allocating resources to the neural network model.

公开(公告)号：US20230127699A1

公开(公告)日：2023-04-27

申请号：US18088872

申请日：2022-12-27

Applicant: BEIJING BAIDU NETCOM SCIENCE TECHNOLOGY CO., LTD.

Inventor： Ji Liu ,  Sunjie Yu ,  Weijia Zhang ,  Hao Liu ,  Hengshu Zhu ,  Dejing Dou ,  Hui Xiong

IPC: G06N20/00 ,  G06Q50/16

Abstract: A method of training a model, a method of determining an asset valuation, a device, a storage medium, and a program product, which relate to a field of artificial intelligence, in particular to fields of deep learning and natural language understanding. A specific implementation can include: determining an event-level representation according to a first set of feature data; performing a multi-task learning for a first model according to the event-level representation, to obtain first price distribution data, and transmitting the first price distribution data to a central server; determining a first intra-region representation according to a second set of feature data; adding a noise signal to the first intra-region representation, and transmitting the noised intra-region representation to a client; and adjusting a parameter of the first model according to a noised parameter gradient in response to the noised parameter gradient being received from the central server.

公开(公告)号：US20220191270A1

公开(公告)日：2022-06-16

申请号：US17687123

申请日：2022-03-04

Applicant: Beijing Baidu Netcom Science Technology Co., Ltd.

Inventor： Ji Liu ,  Xiyue Zhang ,  Haoyi Xiong ,  Dejing Dou ,  Shilei Ji

IPC: H04L67/10 ,  H04L47/78

Abstract: A method of data interaction, a data interaction apparatus, an electronic device and a non-transitory computer readable storage medium are provided, related to field of computer technologies, and in particular to the field of artificial intelligence technologies. When the method of data interaction is applied to the first data platform, the method includes: sending a data request to a second data platform based on a first resource server provided by a cloud or based on a local server; acquiring response data fed back by the second data platform based on a second resource server provided by the cloud; at least one of the first resource server and the second resource server is dynamically created by the cloud.