| Sageflow: Robust federated learning against both stragglers and adversaries J Park, DJ Han, M Choi, J Moon Advances in neural information processing systems 34, 840-851, 2021 | 69 | 2021 |
| FedMes: Speeding up federated learning with multiple edge servers DJ Han, M Choi, J Park, J Moon IEEE Journal on Selected Areas in Communications 39 (12), 3870-3885, 2021 | 25 | 2021 |
| Test-Time Style Shifting: Handling Arbitrary Styles in Domain Generalization J Park, DJ Han, S Kim, J Moon International Conference on Machine Learning (ICML), 2023 | 5 | 2023 |
| Improving Low-Latency Predictions in Multi-Exit Neural Networks via Block-Dependent Losses DJ Han, J Park, S Ham, N Lee, J Moon IEEE Transactions on Neural Networks and Learning Systems, 2023 | 3 | 2023 |
| Style balancing and test-time style shifting for domain generalization J Park, DJ Han, S Kim, J Moon | 2 | 2022 |
| Handling both stragglers and adversaries for robust federated learning J Park, DJ Han, M Choi, J Moon ICML 2021 Workshop on Federated Learning for User Privacy and Data …, 2021 | 2 | 2021 |
| NEO-KD: Knowledge-Distillation-Based Adversarial Training for Robust Multi-Exit Neural Networks S Ham, J Park, DJ Han, J Moon Neural Information Processing Systems (NeurIPS), 2023 | 1 | 2023 |
| Training Multi-Exit Architectures via Block-Dependent Losses for Anytime Inference DJ Han, JW Park, S Ham, N Lee, J Moon 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition …, 2022 | 1 | 2022 |
| StableFDG: Style and Attention Based Learning for Federated Domain Generalization J Park, DJ Han, J Kim, S Wang, CG Brinton, J Moon Neural Information Processing Systems (NeurIPS), 2023 | | 2023 |
| Distribution Aware Active Learning via Gaussian Mixtures Y Park, J Park, DJ Han, W Choi, H Kousar, J Moon | | 2023 |
Dong-Jun HanPurdue Universitypurdue.edu의 이메일 확인됨
