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.

公开(公告)号：US20240005210A1

公开(公告)日：2024-01-04

申请号：US18252559

申请日：2021-11-06

Applicant: Lemon Inc.

Inventor： Jiankai SUN ,  Weihao GAO ,  Chong WANG ,  Hongyi ZHANG ,  Xiaobing LIU ,  Runliang LI ,  Xin YANG

IPC: G06N20/00 ,  G06F21/60

CPC classification number: G06N20/00 ,  G06F21/60

Abstract: The present disclosure relates to a data protection method, an apparatus, a medium and a device. The method includes: acquiring gradient association information respectively corresponding to reference samples of a target batch of an active party of a joint training model; according to the proportion occupied respectively by reference samples of positive examples and reference samples of negative examples in all reference samples of the target batch, determining a constraint condition of the data noise to be added; determining information of said data noise according to the gradient association information and the constraint condition corresponding to the reference samples; correcting, according to the information of said data noise, an initial gradient transmission value corresponding to each reference sample, so as to obtain target gradient transmission information; and sending the target gradient transmission information to a passive party of the joint training model.

公开(公告)号：US20250061507A1

公开(公告)日：2025-02-20

申请号：US18722879

申请日：2023-01-04

Applicant: BEIJING YOUZHUJU NETWORK TECHNOLOGY CO., LTD. ,  LEMON INC.

Inventor： Yuanshun YAO ,  Chong WANG ,  Hang LI

IPC: G06Q30/0601

Abstract: The present disclosure provides a method for obtaining a recommended explanation, a device, and a computer readable medium. The method includes: generating a recommended item by a recommendation model; calculating a similarity between a plurality of explanatory items and the recommended item; obtaining a predetermined number of explanatory items from the plurality of explanatory items, as a recommended explanation of the recommended item, wherein a similarity between the predetermined number of explanatory items and the recommended item is greater than a similarity between other explanatory items and the recommended item; and outputting identification information of the predetermined number of explanatory items.

公开(公告)号：US20250046054A1

公开(公告)日：2025-02-06

申请号：US18717239

申请日：2023-03-17

Applicant: Beijing Bytedance Network Technology Co., Ltd. ,  Lemon Inc.

Inventor： Chong WANG ,  Lin ZHENG

IPC: G06V10/48 ,  G06F17/18

Abstract: The disclosure relates to a method, an apparatus, a storage medium, an electronic device, a computer program product, and a computer program for feature extraction, device. The method includes: determining target data for a feature to be extracted, and determining, based on the target data, a plurality of query vectors, a plurality of key vectors, and a plurality of value vectors; determining a plurality of key-value pair information corresponding to each of the query vectors; and performing, for each of the query vectors, a random mapping based on the query vector and the plurality of data samples, to obtain a plurality of random query vectors, and determining feature information corresponding to the query vector based on the plurality of random query vectors and the plurality of key-value pair information.

公开(公告)号：US20250037806A1

公开(公告)日：2025-01-30

申请号：US18717362

申请日：2023-04-20

Applicant: Beijing Bytedance Network Technology Co., Ltd. ,  Lemon Inc.

Inventor： Xiang GAO ,  Weihao GAO ,  Wenzhi XIAO ,  Zhirui WANG ,  Liang XIANG ,  Chong WANG

IPC: G16C20/70

Abstract: According to implementations of the present disclosure, a method, apparatus, device and medium for managing molecular prediction is provided. In the method, an upstream model is obtained from a portion of network layers in a pretrained model, the pretrained model describing an association between a molecular structure and molecular energy. A downstream model is determined based on a molecular prediction purpose, and an output layer of the downstream model is determined based on the molecular prediction purpose. A molecular prediction model is generated based on the upstream model and the downstream model, the molecular prediction model describing an association between a molecular structure and a molecular prediction purpose associated with the molecular structure. Since the upstream model may have extensive knowledge related to molecules, the amount of training data required to train the molecular prediction model that is generated based on the upstream model and the downstream model may be reduced.

公开(公告)号：US20240249004A1

公开(公告)日：2024-07-25

申请号：US18565000

申请日：2022-04-28

Applicant: Lemon Inc.

Inventor： Xin YANG ,  Jiankai SUN ,  Weihao GAO ,  Junyuan XIE ,  Chong WANG

IPC: G06F21/60 ,  G06N20/20

CPC classification number: G06F21/602 ,  G06N20/20

Abstract: The present disclosure relates to a method and a device for data protection, a readable medium and an electronic apparatus, and the method comprises: acquiring a target identification information union set, wherein the target identification information union set comprises target encryption identification information of a first party of a joint training model and target encryption identification information of a second party of the joint training model, the target encryption identification information in the target identification information union set being obtained by encrypting according to a secret key of the first party and a secret key of the second party; and determining, according to the target identification information union set, a target sample data set for training the joint training model. Therefore, an identification information intersection of the first party and the second party does not need to be determined in advance as in the related technology.

公开(公告)号：US20240220641A1

公开(公告)日：2024-07-04

申请号：US18565962

申请日：2022-07-15

Applicant: Lemon Inc.

Inventor： Jiankai SUN ,  Xin YANG ,  Aonan ZHANG ,  Weihao GAO ,  Junyuan XIE ,  Chong WANG

IPC: G06F21/60 ,  G06N20/00

CPC classification number: G06F21/602 ,  G06N20/00

Abstract: The present disclosure relates to a data protection method, apparatus, medium and electronic device. The method comprises: obtaining a specified batch of reference samples of an active participant of a joint training model; determining generation gradient information of the first reference sample; determining target gradient information sent to the passive participant according to the generation gradient information, and sending the target gradient information to the passive participant, to update, by the passive participant, parameters of the joint training model according to the target gradient information. Through the above solution, the influence of the generated data on the training process and model performance of the joint training model is avoided as much as possible, and the privacy and security of data are improved.

公开(公告)号：US20240126899A1

公开(公告)日：2024-04-18

申请号：US18539851

申请日：2023-12-14

Applicant: Lemon Inc.

Inventor： Xin YANG ,  Junyuan XIE ,  Jiankai SUN ,  Yuanshun YAO ,  Chong WANG

IPC: G06F21/62 ,  G06N3/04 ,  G06N3/098

CPC classification number: G06F21/62 ,  G06N3/04 ,  G06N3/098

Abstract: There are proposed a method, device, apparatus, and medium for protecting sensitive data. In a method, to-be-processed data is received from a server device. A processing result of a user for the to-be-processed data is received, the processing result comprising sensitive data of the user for the processing of the to-be-processed data. A gradient for training a server model at the server device is determined based on a comparison between the processing result and a prediction result for the to-be-processed data. The gradient is updated in a change direction associated with the gradient so as to generate an updated gradient to be sent to the server device. Noise is added only in the change direction associated with the gradient. The corresponding overhead of processing noise in a plurality of directions can be reduced, and no excessive noise data interfering with training will be introduced to the updated gradient.

公开(公告)号：US20240119341A1

公开(公告)日：2024-04-11

申请号：US17953255

申请日：2022-09-26

Applicant: Lemon Inc.

Inventor： Xin YANG ,  Hanlin ZHU ,  Tianyi LIU ,  Jiankai SUN ,  Yuanshun YAO ,  Aonan ZHANG ,  Chong WANG

IPC: G06N20/00

CPC classification number: G06N20/00

Abstract: The present disclosure describes techniques for determining performance of a classifier. A first machine learning model and a second machine learning model may be trained by aggregating updates to the first machine learning model and the second machine learning model received from a plurality of client computing devices. A cumulative distribution function (CDF) associated with a distribution of the positive samples in the user data may be estimated using the trained first machine learning model. A probability density function (PDF) associated with a distribution of the negative samples in the user data may be estimated using the trained second machine learning model. An integration-based computation of an area under the receiver operating characteristic curve (AUC) of the classifier may be performed using the PDF and the CDF.

公开(公告)号：US20240242089A1

公开(公告)日：2024-07-18

申请号：US18565015

申请日：2022-04-28

Applicant: Lemon Inc.

Inventor： Jiankai SUN ,  Weihao GAO ,  Junyuan XIE ,  Chong WANG

IPC: G06N3/098 ,  G06N3/04

CPC classification number: G06N3/098 ,  G06N3/04

Abstract: The present disclosure relates to a data protection method, a training method and apparatus for a network structure, a medium, and a device. The data protection method includes: obtaining original feature information of a target batch of reference samples for a passive party of a joint training model; and processing the original feature information by means of a target feature processing network structure to obtain target feature information corresponding to the original feature information. A neural network structure is trained by at least aiming at minimizing a coupling degree of between original training feature information and target training feature information of training samples for the passive party to obtain the target feature processing network structure. The target training feature information is feature information corresponding to the original training feature information that is outputted from the neural network structure using the original training feature information as an input.