| Xtarnet: Learning to extract task-adaptive representation for incremental few-shot learning SW Yoon*, DY Kim*, J Seo, J Moon, (*equal contribution) International Conference on Machine Learning, 10852-10860, 2020 | 65 | 2020 |
| Warping the space: Weight space rotation for class-incremental few-shot learning DY Kim, DJ Han, J Seo, J Moon The Eleventh International Conference on Learning Representations, 2023 | 52 | 2023 |
| SplitGP: Achieving both generalization and personalization in federated learning DJ Han, DY Kim, M Choi, CG Brinton, J Moon IEEE INFOCOM 2023-IEEE Conference on Computer Communications, 1-10, 2023 | 32 | 2023 |
| Few-round learning for federated learning Y Park*, DJ Han*, DY Kim, J Seo, J Moon, (*equal contribution) Advances in Neural Information Processing Systems 34, 28612-28622, 2021 | 22 | 2021 |
| 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 | 10 | 2023 |
| Achieving Lossless Gradient Sparsification via Mapping to Alternative Space in Federated Learning DY Kim, DJ Han, J Seo, J Moon Forty-first International Conference on Machine Learning, 2024 | 2 | 2024 |
| Deep Neural Network Compression for Image Inpainting S Kim, DY Kim, J Moon European Conference on Computer Vision, 99-114, 2022 | | 2022 |
| Few-Round Learning for Federated Learning (Supplementary Material) Y Park, DJ Han, DY Kim, J Seo, J Moon | | |