Jungwuk Park

According to our database, Jungwuk Park authored at least 7 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Improving Low-Latency Predictions in Multi-Exit Neural Networks via Block-Dependent Losses.

Dong-Jun Han, Jungwuk Park, Seokil Ham, Namjin Lee, Jaekyun Moon

IEEE Trans. Neural Networks Learn. Syst., November, 2024

Consistency-Guided Temperature Scaling Using Style and Content Information for Out-of-Domain Calibration.

Wonjeong Choi, Jungwuk Park, Dong-Jun Han, Younghyun Park, Jaekyun Moon

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

StableFDG: Style and Attention Based Learning for Federated Domain Generalization.

Jungwuk Park, Dong-Jun Han, Jinho Kim, Shiqiang Wang, Christopher G. Brinton, Jaekyun Moon

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

NEO-KD: Knowledge-Distillation-Based Adversarial Training for Robust Multi-Exit Neural Networks.

Seokil Ham, Jungwuk Park, Dong-Jun Han, Jaekyun Moon

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Test-Time Style Shifting: Handling Arbitrary Styles in Domain Generalization.

Jungwuk Park, Dong-Jun Han, Soyeong Kim, Jaekyun Moon

Proceedings of the International Conference on Machine Learning, 2023

2021

FedMes: Speeding Up Federated Learning With Multiple Edge Servers.

Dong-Jun Han, Minseok Choi, Jungwuk Park, Jaekyun Moon

IEEE J. Sel. Areas Commun., 2021

Sageflow: Robust Federated Learning against Both Stragglers and Adversaries.

Jungwuk Park, Dong-Jun Han, Minseok Choi, Jaekyun Moon

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021