Learning with Noisy Labels via Sparse Regularization X Zhou, X Liu, C Wang, D Zhai, J Jiang, X Ji
ICCV 2021, 2021
77 2021 Asymmetric Loss Functions for Learning with Noisy Labels X Zhou, X Liu, J Jiang, X Gao, X Ji
Proceedings of the 38th International Conference on Machine Learning 139 …, 2021
74 2021 Asymmetric loss functions for noise-tolerant learning: Theory and applications X Zhou, X Liu, D Zhai, J Jiang, X Ji
IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (7), 8094-8109, 2023
44 2023 No one idles: Efficient heterogeneous federated learning with parallel edge and server computation F Zhang, X Liu, S Lin, G Wu, X Zhou, J Jiang, X Ji
International Conference on Machine Learning, 41399-41413, 2023
14 2023 Learning Towards the Largest Margins X Zhou, X Liu, D Zhai, J Jiang, X Gao, X Ji
The Tenth International Conference on Learning Representations, 2022
14 2022 Prototype-Anchored Learning for Learning with Imperfect Annotations X Zhou, X Liu, D Zhai, J Jiang, X Gao, X Ji
Proceedings of the 39th International Conference on Machine Learning, 27245 …, 2022
6 2022 Resmooth: Detecting and utilizing ood samples when training with data augmentation C Wang, J Jiang, X Zhou, X Liu
IEEE Transactions on Neural Networks and Learning Systems, 2022
5 2022 Variance-enlarged Poisson Learning for Graph-based Semi-Supervised Learning with Extremely Sparse Labeled Data X Zhou, X Liu, H Yu, J Wang, Z Xie, J Jiang, X Ji
The Twelfth International Conference on Learning Representations, 2024
4 2024 Mix-ddpm: Enhancing diffusion models through fitting mixture noise with global stochastic offset H Wang, D Zhai, X Zhou, J Jiang, X Liu
ACM Transactions on Multimedia Computing, Communications and Applications 20 …, 2024
2 2024 Zero-Mean Regularized Spectral Contrastive Learning: Implicitly Mitigating Wrong Connections in Positive-Pair Graphs X Zhou, X Liu, F Zhang, G Wu, D Zhai, J Jiang, X Ji
The Twelfth International Conference on Learning Representations, 2024
2 2024 On the dynamics under the unhinged loss and beyond X Zhou, X Liu, H Wang, D Zhai, X Ji
Journal of Machine Learning Research 24 (376), 1-62, 2023
2 2023 GM-DDPM: Denoising diffusion probabilistic models with Gaussian Mixture Noise H Wang, X Liu, X Zhou, J Jiang, D Zhai, W Gao
1 2023 J Wang, X Zhou, D Zhai, J Jiang, X Ji, X Liu
Advances in Neural Information Processing Systems 37, 32012-32038, 2024
2024 Neural Field Classifiers via Target Encoding and Classification Loss X Yang, Z Xie, X Zhou, B Liu, B Liu, Y Liu, H Wang, Y CAI, M Sun
The Twelfth International Conference on Learning Representations, 2024
2024 Variation-Bounded Losses for Learning with Noisy Labels J Wang, X Zhou, G Hu, D Zhai, J Jiang, X Ji, X Liu
Parallel Federated Learning over Heterogeneous Devices F Zhang, X Liu, S Lin, G Wu, X Zhou, J Jiang, X Ji
On the Dynamics under the Averaged Sample Margin Loss and Beyond X Zhou, X Liu, H Wang, D Zhai, J Jiang, X Ji
