JICS

1. Federated learning-based client training acceleration method for personalized digital twins

YoungHwan Jeong, Won-gi Choi, Hyoseon Kye, JeeHyeong Kim, Min-hwan Song, Sang-shin Lee, Vol. 25, No. 4, pp. 23-37, Aug. 2024

10.7472/jksii.2024.25.4.23
Keywords: Digital Twin, Federated learning, Vector database, training optimization, Privacy, similarity search

2. Effective Adversarial Training by Adaptive Selection of Loss Function in Federated Learning

Suchul Lee, Vol. 25, No. 2, pp. 1-9, Apr. 2024

10.7472/jksii.2024.25.2.1
Keywords: Federated learning, adversarial attacks, adversarial training, trade-off relationship

3. FedGCD: Federated Learning Algorithm with GNN based Community Detection for Heterogeneous Data

Wooseok Shin, Jitae Shin, Vol. 24, No. 6, pp. 1-11, Dec. 2023

10.7472/jksii.2023.24.6.1
Keywords: Federated learning, Non-IID, data heterogeneity, community detection, Graph Neural Networks

4. Advances and Issues in Federated Learning Open Platforms: A Systematic Comparison and Analysis

JinSoo Kim, SeMo Yang, KangYoon Lee, KwangKee Lee, Vol. 24, No. 4, pp. 1-13, Aug. 2023

10.7472/jksii.2023.24.4.1
Keywords: Federated learning, Distributed Learning, FL Framework, Open Source

5. Efficient distributed consensus optimization based on patterns and groups for federated learning

Seung Ju Kang, Ji Young Chun, Geontae Noh, Ik Rae Jeong, Vol. 23, No. 4, pp. 73-85, Aug. 2022

10.7472/jksii.2022.23.4.73
Keywords: Federated learning, Optimization, Weight model, Communication time, Privacy, ADMM

6. Efficient Resource Slicing Scheme for Optimizing Federated Learning Communications in Software-Defined IoT Networks

Prohim Tam, Sa Math, Seokhoon Kim, Vol. 22, No. 5, pp. 27-33, Oct. 2021

10.7472/jksii.2021.22.5.27
Keywords: Deep Learning, Federated learning, Internet of Things, Network Functions Virtualization, Software-Defined Networking

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