公开(公告)号：US20230418794A1

公开(公告)日：2023-12-28

申请号：US18252926

申请日：2021-11-06

Applicant: Lemon Inc.

Inventor： Chenliaohui FANG ,  Junyuan XIE ,  Lele YU ,  Xiaobing LIU ,  Di WU

IPC: G06F16/215 ,  G06F21/60

CPC classification number: G06F16/215 ,  G06F21/602

Abstract: The present disclosure relates to a data processing method, non-transitory medium and electronic device. The method includes: acquiring first user data and second user data, and initializing a first time window corresponding to the first user data and first time information corresponding to the first time window, as well as a second time window corresponding to the second user data and second time information corresponding to the second time window; determining first data and the first time information corresponding to the first time window based on the first user data; determining second data and the second time information corresponding to the second time window based on the second user data; based on the first data and the second data, determining alignment data corresponding to a same user from the first user data and the second user data.

公开(公告)号：US20230418470A1

公开(公告)日：2023-12-28

申请号：US18252982

申请日：2021-11-15

Applicant: LEMON INC.

Inventor： Liangchao WU ,  Junyuan XIE ,  Lizhe ZHANG ,  Di WU ,  Xiaobing LIU

IPC: G06F3/06

CPC classification number: G06F3/0604 ,  G06F3/0638 ,  G06F3/0683

Abstract: Disclosed in the embodiments of the present disclosure are a data processing method and apparatus, and an electronic device. A specific implementation of the method comprises: determining a target first storage region from among a preset number of first storage regions; on the basis of a interaction process with a second device, determining identical target identification information comprised in the target first storage region and a target second storage region, and determining whether the interaction process meets a target requirement; and in response to the interaction process meeting the target requirement, storing target first data identified by the target identification information, so that the second device stores target second data identified by the target identification information. Thus, the target first data and the target second data identified by the same target identification information in the target first storage region and the target second storage region are aligned.

公开(公告)号：US20240012641A1

公开(公告)日：2024-01-11

申请号：US18252942

申请日：2021-11-16

Applicant: Lemon Inc.

Inventor： Ruoxing HUANG ,  Junyuan XIE ,  Longyijia LI ,  Chenliaohui FANG ,  Shihao SHEN ,  Lei SHI ,  Lingyuan ZHANG ,  Peng ZHAO ,  Deliang FAN ,  Di WU ,  Xiaobing LIU

IPC: G06F8/71 ,  H04L9/40 ,  G06N3/098 ,  G06F16/955

CPC classification number: G06F8/71 ,  H04L63/101 ,  G06N3/098 ,  G06F16/9558

Abstract: A model construction method and an apparatus, and a medium and an electronic device are disclosed. The method is applied to a first participant platform, and includes: associating first configuration information pre-created by a first participant with second configuration information pre-created by a second participant; verifying the first configuration information; sending, to a second participant platform corresponding to the second participant, a second creation request for requesting the creation of the federated learning model, to cause the second participant platform to verify the second configuration information creating a first model task on the basis of a first parameter corresponding to the first configuration information; and performing co-training on the basis of the first model task and a second model task, to obtain the federated learning model.

公开(公告)号：US20250044783A1

公开(公告)日：2025-02-06

申请号：US18713988

申请日：2022-11-07

Applicant: Lemon Inc.

Inventor： Weihao GAO ,  Ce YANG ,  Di WU ,  Chong WANG

IPC: G05B23/02

Abstract: According to embodiments of the present disclosure, there are provided a method, device, medium, and product for state prediction. The method includes: obtaining a neural network, the neural network being trained to determine a state change of a physical system over time, training data of the neural network indicating states of a plurality of physical systems at a plurality of times; obtaining state data corresponding to a state of a target physical system at a first time; determining respective unit feature representations of the physical units in the target physical system based at least on target values of material properties of the physical units; and determining a state of the target physical system at a second time based on the state data by inputting at least the unit feature representations to the neural network. Through the above solution, generalization capability of the neural network can be significantly improved.