Boosting co-teaching with compression regularization for label noise Y Chen, X Shen, SX Hu, JAK Suykens Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 54 | 2021 |
Jigsaw-vit: Learning jigsaw puzzles in vision transformer Y Chen, X Shen, Y Liu, Q Tao, JAK Suykens Pattern Recognition Letters 166, 53-60, 2023 | 17 | 2023 |
Compressing features for learning with noisy labels Y Chen, SX Hu, X Shen, C Ai, JAK Suykens IEEE Transactions on Neural Networks and Learning Systems 35 (2), 2124-2138, 2022 | 16 | 2022 |
Primal-attention: Self-attention through asymmetric kernel svd in primal representation Y Chen, Q Tao, F Tonin, JAK Suykens Advances in Neural Information Processing Systems 36, 2024 | 14 | 2024 |
Fast learning in reproducing kernel krein spaces via signed measures F Liu, X Huang, Y Chen, JAK Suykens International Conference on Artificial Intelligence and Statistics, 388-396, 2021 | 9 | 2021 |
Learning in Feature Spaces via Coupled Covariances: Asymmetric Kernel SVD and Nyström Method Q Tao, F Tonin, A Lambert, Y Chen, P Patrinos, JAK Suykens International Conference on Machine Learning, 2024 | 1 | 2024 |
SURE: SUrvey REcipes for building reliable and robust deep networks Y Li, Y Chen, X Yu, D Chen, X Shen Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | | 2024 |
Self-Attention through Kernel-Eigen Pair Sparse Variational Gaussian Processes Y Chen, Q Tao, F Tonin, JAK Suykens International Conference on Machine Learning, 2024 | | 2024 |
Two-stage Best-scored Random Forest for Large-scale Regression H Hang, Y Chen, JAK Suykens arXiv preprint arXiv:1905.03438, 2019 | | 2019 |