公开(公告)号：US20250086496A1

公开(公告)日：2025-03-13

申请号：US18404143

申请日：2024-01-04

Applicant: FOUNDATION OF SOONGSIL UNIVERSITY-INDUSTRY COOPERATION

Inventor： Min Hae KWON ,  Mi Ru KIM ,  Hee Won PARK

IPC: G06N20/00

Abstract: A method and apparatus for augmenting knowledge using federated learning information. An apparatus for augmenting knowledge using federated learning information comprises a transceiver unit that receives local information including a global parameter of a local model, a local latent vector, and a local loss value from each of a plurality of individual devices, a data storage unit that stores the local information, a federated learning execution unit that collects a global parameter of the local model and generates a federated global parameter for a global model, and a large model learning unit that generates a true label approximate value for learning a large model using the local information and the federated global parameter, and learns the large model using a prediction result obtained by inputting the local latent vector into the large model and the true label approximate value.

公开(公告)号：US20240242088A1

公开(公告)日：2024-07-18

申请号：US18219691

申请日：2023-07-09

Applicant: FOUNDATION OF SOONGSIL UNIVERSITY-INDUSTRY COOPERATION

Inventor： Min Hae KWON ,  Mi Ru KIM ,  Hyo Seon KYE

IPC: G06N3/098

CPC classification number: G06N3/098

Abstract: Provided is a method of personalized federated learning performed by an electronic device. The method is performed by an electronic device including one or more processors, a communication circuit which communicates with an external device, and one or more memories storing at least one instruction executed by the one or more processors. The method may include, by the one or more processors, training a local model using local data, in which the local model as an artificial neural network model includes a first parameter set corresponding to a global parameter set and a second parameter set corresponding to a local parameter set, transmitting the first parameter set to the external device, receiving a 1-1st parameter set for renewing the first parameter set from the external device, changing the first parameter set included in the local model to the 1-1st parameter set, and training the local model including the 1-1st parameter set.

公开(公告)号：US20240241800A1

公开(公告)日：2024-07-18

申请号：US18219642

申请日：2023-07-07

Applicant: FOUNDATION OF SOONGSIL UNIVERSITY-INDUSTRY COOPERATION

Inventor： Min Hae KWON ,  Mi Ru KIM

IPC: G06F11/14

CPC classification number: G06F11/1471

Abstract: Provided is an anomaly detection method performed by an electronic device. The method performed by an electronic device including one or more processors, a communication circuit which communicates with an external device, and one or more memories storing at least one instruction executed by the one or more processors may include: by the one or more processors, receiving target data for discriminating whether an anomaly occurs, in which the target data includes a value for each of a plurality of features; inputting a value for at least one important feature among the plurality of features into an anomaly detection model, in which the at least one important feature is determined by important feature information received from the external device; and determining whether the target data is abnormal based on an output of the anomaly detection model.