| Sageflow: Robust federated learning against both stragglers and adversaries J Park, DJ Han, M Choi, J Moon Neural Information Processing Systems (NeurIPS), 2021 | 78 | 2021 |
| Communication-computation efficient secure aggregation for federated learning B Choi, J Sohn, DJ Han, J Moon arXiv preprint arXiv:2012.05433, 2020 | 65 | 2020 |
| Accelerating federated learning with split learning on locally generated losses DJ Han, HI Bhatti, J Lee, J Moon ICML Workshop on Federated Learning for User Privacy and Data Confidentiality, 2021 | 54 | 2021 |
| Election coding for distributed learning: Protecting signsgd against byzantine attacks J Sohn, DJ Han, B Choi, J Moon Neural Information Processing Systems (NeurIPS), 2020 | 40 | 2020 |
| Scalable network-coded PBFT consensus algorithm B Choi, J Sohn, DJ Han, J Moon IEEE International Symposium on Information Theory (ISIT), 2019 | 27 | 2019 |
| FedMes: Speeding up federated learning with multiple edge servers DJ Han, M Choi, J Park, J Moon IEEE Journal on Selected Areas in Communications, 2021 | 26 | 2021 |
| Warping the Space: Weight Space Rotation for Class-Incremental Few-Shot Learning DY Kim, DJ Han, J Seo, J Moon International Conference on Learning Representations (ICLR), 2023 | 25 | 2023 |
| Probabilistic caching and dynamic delivery policies for categorized contents and consecutive user demands M Choi, AF Molisch, DJ Han, D Kim, J Kim, J Moon IEEE Transactions on Wireless Communications, 2020 | 21 | 2020 |
| Bi-directional cooperative NOMA without full CSIT M Choi, DJ Han, J Moon IEEE Transactions on Wireless Communications, 2018 | 18 | 2018 |
| Active Learning for Object Detection with Evidential Deep Learning and Hierarchical Uncertainty Aggregation Y Park, S Kim, W Choi, DJ Han, J Moon International Conference on Learning Representations (ICLR), 2023 | 17 | 2023 |
| SplitGP: Achieving Both Generalization and Personalization in Federated Learning DJ Han, DY Kim, M Choi, CG Brinton, J Moon IEEE International Conference on Computer Communications (INFOCOM), 2023 | 15 | 2023 |
| Few-Round Learning for Federated Learning Y Park, DJ Han, DY Kim, J Seo, M Jaekyun Neural Information Processing Systems (NeurIPS), 2021 | 15 | 2021 |
| Coded wireless distributed computing with packet losses and retransmissions DJ Han, JY Sohn, J Moon IEEE Transactions on Wireless Communications, 2021 | 15 | 2021 |
| Coded distributed computing over packet erasure channels DJ Han, J Sohn, J Moon IEEE International Symposium on Information Theory (ISIT), 2019 | 14 | 2019 |
| Probabilistic caching policy for categorized contents and consecutive user demands M Choi, D Kim, DJ Han, J Kim, J Moon IEEE International Conference on Communications (ICC), 2019 | 9 | 2019 |
| Hierarchical broadcast coding: Expediting distributed learning at the wireless edge DJ Han, JY Sohn, J Moon IEEE Transactions on Wireless Communications, 2020 | 8 | 2020 |
| Combined subband-subcarrier spectral shaping in multi-carrier modulation under the excess frame length constraint DJ Han, J Moon, D Kim, SY Chung, YH Lee IEEE Journal on Selected Areas in Communications, 2017 | 8 | 2017 |
| FedMFS: Federated Multimodal Fusion Learning with Selective Modality Communication L Yuan, DJ Han, VP Chellapandi, SH Żak, CG Brinton IEEE International Conference on Communications (ICC), 2023 | 7 | 2023 |
| Submodel Partitioning in Hierarchical Federated Learning: Algorithm Design and Convergence Analysis W Fang, DJ Han, CG Brinton IEEE International Conference on Communications (ICC), 2023 | 6 | 2023 |
| Federated Split Learning With Joint Personalization-Generalization for Inference-Stage Optimization in Wireless Edge Networks DJ Han, DY Kim, M Choi, D Nickel, J Moon, M Chiang, CG Brinton IEEE Transactions on Mobile Computing, 2023 | 5 | 2023 |
Jaekyun MoonUniversity of Minnesota, KAIST, Carnegie Mellon University在 kaist.edu 的电子邮件经过验证
