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：US12140441B2

公开(公告)日：2024-11-12

申请号：US17531529

申请日：2021-11-19

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

Inventor： Weijia Zhang ,  Hao Liu ,  Dejing Dou ,  Hui Xiong

IPC: G01C21/34 ,  G06N20/00 ,  G06Q30/0601 ,  H04L67/12

Abstract: A method for recommending a station for a vehicle, a device, and a storage medium are provided. The method comprises: receiving, by a server, an access request from a vehicle; obtaining, based on the access request, a plurality of observation values from a plurality of stations associated with the vehicle, respectively, each observation value is based on a corresponding pre-trained recommendation model, each observation value includes factors associated with access of the vehicle to the station corresponding to the observation value; determining, an action value for the station based on the observation value and the pre-trained recommendation model for the station, the action value for the station indicates a matching degree between the access request and the station; determining a recommended station among the plurality of stations based on the action values of the plurality of stations; and sending to the vehicle an instruction of driving to the recommended station.