| How does disagreement help generalization against label corruption? X Yu, B Han, J Yao, G Niu, IW Tsang, M Sugiyama International Conference on Machine Learning, 2019 | 335 | 2019 |
| Masking: A new perspective of noisy supervision B Han*, J Yao*, G Niu, M Zhou, I Tsang, Y Zhang, M Sugiyama Advances in Neural Information Processing Systems, 5836-5846, 2018 | 156 | 2018 |
| Deep learning from noisy image labels with quality embedding J Yao, J Wang, IW Tsang, Y Zhang, J Sun, C Zhang, R Zhang IEEE Transactions on Image Processing 28 (4), 1909-1922, 2018 | 62 | 2018 |
| Safeguarded dynamic label regression for noisy supervision J Yao, H Wu, Y Zhang, IW Tsang, J Sun Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 9103-9110, 2019 | 43 | 2019 |
| Collaborative learning for weakly supervised object detection J Wang, J Yao, Y Zhang, R Zhang IJCAI, 2018 | 36 | 2018 |
| Sparse-interest network for sequential recommendation Q Tan, J Zhang, J Yao, N Liu, J Zhou, H Yang, X Hu Proceedings of the 14th ACM International Conference on Web Search and Data …, 2021 | 25 | 2021 |
| Joint latent Dirichlet allocation for social tags J Yao, Y Wang, Y Zhang, J Sun, J Zhou IEEE Transactions on Multimedia 20 (1), 224-237, 2017 | 24 | 2017 |
| Learning on Attribute-Missing Graphs X Chen, S Chen, J Yao, H Zheng, Y Zhang, IW Tsang IEEE transactions on pattern analysis and machine intelligence, 2020 | 15 | 2020 |
| Bayes embedding (bem) refining representation by integrating knowledge graphs and behavior-specific networks Y Ye, X Wang, J Yao, K Jia, J Zhou, Y Xiao, H Yang Proceedings of the 28th ACM international conference on information and …, 2019 | 15 | 2019 |
| Degeneration in vae: in the light of fisher information loss H Zheng, J Yao, Y Zhang, IW Tsang arXiv preprint arXiv:1802.06677, 2018 | 13 | 2018 |
| Understanding vaes in fisher-shannon plane H Zheng, J Yao, Y Zhang, IW Tsang, J Wang Proceedings of the AAAI conference on artificial intelligence 33 (01), 5917-5924, 2019 | 11 | 2019 |
| Device-Cloud Collaborative Learning for Recommendation J Yao, F Wang, KY Jia, B Han, J Zhou, H Yang KDD 2021, 2021 | 10 | 2021 |
| Variational collaborative learning for user probabilistic representation K Cui, X Chen, J Yao, Y Zhang AAAI workshop, 2018 | 7 | 2018 |
| Edge-Cloud Polarization and Collaboration: A Comprehensive Survey for AI J Yao, S Zhang, Y Yao, F Wang, J Ma, J Zhang, Y Chu, L Ji, K Jia, T Shen, ... IEEE Transactions on Knowledge and Data Engineering, 2022 | 6 | 2022 |
| Discovering user interests from social images J Yao, Y Zhang, I Tsang, J Sun International Conference on Multimedia Modeling, 160-172, 2017 | 6 | 2017 |
| Contrastive attraction and contrastive repulsion for representation learning H Zheng, X Chen, J Yao, H Yang, C Li, Y Zhang, H Zhang, I Tsang, J Zhou, ... arXiv preprint arXiv:2105.03746, 2021 | 4* | 2021 |
| Learning with group noise Q Wang*, J Yao*, C Gong, T Liu, M Gong, H Yang, B Han Proceedings of the AAAI Conference on Artificial Intelligence, 2021 | 4 | 2021 |
| Preference aware recommendation based on categorical information Z Rao, J Yao, Y Zhang, R Zhang International Conference on Machine Learning and Applications, 865-870, 2016 | 4 | 2016 |
| Click-through Rate Prediction with Auto-Quantized Contrastive Learning Y Pan, J Yao, B Han, K Jia, Y Zhang, H Yang arXiv preprint arXiv:2109.13921, 2021 | 3 | 2021 |
| Decoupled Variational Embedding for Signed Directed Networks X Chen, J Yao, M Li, Y Zhang, Y Wang ACM Transactions on the Web, 2020 | 3 | 2020 |
Ya ZhangShanghai Jiao Tong University確認したメール アドレス: sjtu.edu.cn
