Y. Lee, H. Lee, J. Gong, C. Yang, and J. Kang*, “Debunking Optimization Myths in Federated Learning for Medical Image Classification” in Proc. EMA4MICCAI Workshop, 2025.
Y. Lee, J. Gong, and J. Kang*, “Improving Generalizability of Kolmogorov-Arnold Networks via Error-Correcting Output Codes”, in Proc. IEEE Biomedical Circuits and Systems Conference (BioCAS), 2025.
Y. Lee, J. Gong, and J. Kang*, “Embedding Byzantine Fault Tolerance into Federated Learning via Consistency Scoring Plugin”, in Proc. G(GlobeCom), 2025.
Y. Lee, J. Gong, S. Choi, and J. Kang*, “Revisit the Stability of Vanilla Federated Learning Under Diverse Conditions,” in Proc. Int. Conf. on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2025.
J. Gong, J. Kang, O. Simeone, and R. Kassab, “Forget-SVGD: Particle-based Bayesian federated unlearning”, in 2022 IEEE Data Science and Learning Workshop (DSLW), 2022, pp. 1–6.
J. Kim, J. Gong, S. Kim, and J. Kang, “Secure UAV Communications with Transmit-array Antenna”, in 2022 IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia), IEEE, 2022, pp. 1–4.
J. Gong, O. Simeone, and J. Kang, “Bayesian variational federated learning and unlearning in decentralized networks”, in 2021 IEEE 22nd International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2021, pp. 216–220.