| Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation T Kim, J Oh, NY Kim, S Cho, SY Yun IJCAI 2021, 2021 | 219 | 2021 |
| FINE Samples for Learning with Noisy Labels T Kim, J Ko, J Choi, S Cho, SY Yun NeurIPS 2021, 2021 | 114 | 2021 |
| Revisiting orthogonality regularization: a study for convolutional neural networks in image classification T Kim, SY Yun IEEE Access 10, 69741-69749, 2022 | 16 | 2022 |
| A Survey of Supernet Optimization and its Applications: Spatial and Temporal Optimization for Neural Architecture Search S Cha, T Kim, H Lee, SY Yun arXiv preprint arXiv:2204.03916, 2022 | 14* | 2022 |
| Instructive Decoding: Instruction-Tuned Large Language Models are Self-Refiner from Noisy Instructions T Kim, J Kim, G Lee, SY Yun ICLR 2024 (Spotlight) (Prelim: NeurIPS 2023 Instruction Workshop), 2024 | 13* | 2024 |
| Accurate and fast federated learning via combinatorial multi-armed bandits T Kim, S Bae, J Lee, S Yun arXiv, 2020 | 12 | 2020 |
| Benchmark Dataset for Precipitation Forecasting by Post-Processing the Numerical Weather Prediction T Kim, N Ho, D Kim, SY Yun arXiv, 2022 | 9 | 2022 |
| Weather4cast at NeurIPS 2022: Super-Resolution Rain Movie Prediction under Spatio-temporal Shifts A Gruca, F Serva, L Lliso, P Rípodas, X Calbet, P Herruzo, J Pihrt, ... NeurIPS 2022 Competition Track, 292-313, 2023 | 8 | 2023 |
| Navigating Data Heterogeneity in Federated Learning: A Semi-Supervised Federated Object Detection T Kim, E Lin, J Lee, C Lau, V Mugunthan NeurIPS 2023, 2023 | 7* | 2023 |
| Supernet Training for Federated Image Classification under System Heterogeneity T Kim, SY Yun ICML 2022 Workshop: Dynamic Neural Networks (Oral), 2022 | 7 | 2022 |
| Accelerating Blockwise Parallel Language Models with Draft Refinement T Kim, AT Suresh, KA Papineni, M Riley, S Kumar, A Benton NeurIPS 2024, 2024 | 4* | 2024 |
| Region-Conditioned Orthogonal 3D U-Net for Weather4Cast Competition T Kim, S Kang, H Shin, D Yoon, S Eom, K Shin, SY Yun NeurIPS 2022 Workshop: Weather4Cast Competition, 2022 | 4 | 2022 |
| Efficient Model for Image Classification With Regularization Tricks T Kim, J Kim, S Yun NeurIPS 2019 Competition and Demonstration Track (PMLR 123), 2020 | 3 | 2020 |
| Block Transformer: Global-to-Local Language Modeling for Fast Inference N Ho, S Bae, T Kim, H Jo, Y Kim, T Schuster, A Fisch, J Thorne, SY Yun NeurIPS 2024, 2024 | 2 | 2024 |
| Leveraging Normalization Layer in Adapters With Progressive Learning and Adaptive Distillation for Cross-Domain Few-Shot Learning Y Yang, T Kim, SY Yun AAAI 2024, 2024 | 2 | 2024 |
| Revisiting Architecture-aware Knowledge Distillation: Smaller Models and Faster Search T Kim, H Myeong, SY Yun ICML 2022 Workshop: Hardware Aware Efficient Training (HAET), 2022 | 2 | 2022 |
| Adaptive Local Bayesian Optimization Over Multiple Discrete Variables T Kim, J Ahn, N Kim, S Yun NeurIPS 2020 Workshop at Competition Track: Black-Box Optimization Challenge, 2020 | 2 | 2020 |
| FLR: Label-Mixture Regularization for Federated Learning with Noisy Labels T Kim, D Kim, SY Yun TMLR, 2024 | 1* | 2024 |
| Revisiting the Activation Function for Federated Image Classification J Shin, T Kim, SY Yun NeurIPS 2022 Workshop: Federated Learning, 2022 | 1 | 2022 |
| Layover Intermediate Layer for Multi-Label Classification in Efficient Transfer Learning S Eom, T Kim, SY Yun NeurIPS 2022 Workshop: Has it Trained Yet?, 2022 | 1 | 2022 |
Se Young YunKAISTVerified email at kaist.ac.kr
