Relational knowledge distillation W Park, D Kim, Y Lu, M Cho Proceedings of the IEEE/CVF conference on computer vision and pattern
, 2019 | 1572 | 2019 |
Groupface: Learning latent groups and constructing group-based representations for face recognition Y Kim, W Park, MC Roh, J Shin Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern
, 2020 | 121 | 2020 |
GRPE: Relative Positional Encoding for Graph Transformer W Park*, WG Chang*, D Lee, J Kim, S Hwang ICLR2022 Machine Learning for Drug Discovery, 2022 | 63 | 2022 |
BroadFace: Looking at Tens of Thousands of People at Once for Face Recognition Y Kim*, W Park*, J Shin European Conference on Computer Vision (ECCV), 2020 | 52 | 2020 |
Multi-level Distance Regularization for Deep Metric Learning Y Kim*, W Park* Association for the Advancement of Artificial Intelligence (AAAI), 2021 | 16 | 2021 |
Diversified Mutual Learning for Deep Metric Learning W Park*, W Kim*, K You, M Cho European Conference on Computer Vision, 709-725, 2020 | 10 | 2020 |
Discrete Infomax Codes for Supervised Representation Learning Y Lee, W Kim, W Park, S Choi Entropy 24 (4), 501, 2022 | 5 | 2022 |
JaxPruner: A concise library for sparsity research JH Lee, W Park, NE Mitchell, J Pilault, JSO Ceron, HB Kim, N Lee, ... Conference on Parsimony and Learning, 515-528, 2024 | 4 | 2024 |
Prefixing Attention Sinks can Mitigate Activation Outliers for Large Language Model Quantization S Son, W Park, W Han, K Kim, J Lee arXiv preprint arXiv:2406.12016, 2024 | 1 | 2024 |
Rethinking Pruning Large Language Models: Benefits and Pitfalls of Reconstruction Error Minimization S Shin, W Park, J Lee, N Lee arXiv preprint arXiv:2406.15524, 2024 | | 2024 |
Regularizing Neural Networks via Stochastic Branch Layers W Park*, PH Seo*, B Han, M Cho Asian Conference on Machine Learning (ACML), 2019 | | 2019 |