DeepFish: Accurate underwater live fish recognition with a deep architecture H Qin, X Li, J Liang, Y Peng, C Zhang Neurocomputing 187, 49-58, 2016 | 264 | 2016 |
An rnn architecture with dynamic temporal matching for personalized predictions of parkinson's disease C Che, C Xiao, J Liang, B Jin, J Zho, F Wang Proceedings of the 2017 SIAM international conference on data mining, 198-206, 2017 | 153 | 2017 |
Data-driven subtyping of Parkinson’s disease using longitudinal clinical records: a cohort study X Zhang, J Chou, J Liang, C Xiao, Y Zhao, H Sarva, C Henchcliffe, ... Scientific reports 9 (1), 797, 2019 | 147 | 2019 |
Causality inspired representation learning for domain generalization F Lv, J Liang, S Li, B Zang, CH Liu, Z Wang, D Liu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 129 | 2022 |
Bi-classifier determinacy maximization for unsupervised domain adaptation S Li, F Lv, B Xie, CH Liu, J Liang, C Qin Proceedings of the AAAI conference on artificial intelligence 35 (10), 8455-8464, 2021 | 98 | 2021 |
Semantic concentration for domain adaptation S Li, M Xie, F Lv, CH Liu, J Liang, C Qin, W Li Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 86 | 2021 |
Addressing algorithmic disparity and performance inconsistency in federated learning S Cui, W Pan, J Liang, C Zhang, F Wang Advances in Neural Information Processing Systems 34, 26091-26102, 2021 | 69 | 2021 |
Weakly-and semi-supervised object detection with expectation-maximization algorithm Z Yan, J Liang, W Pan, J Li, C Zhang arXiv preprint arXiv:1702.08740, 2017 | 55 | 2017 |
Predicting seizures from electroencephalography recordings: a knowledge transfer strategy J Liang, R Lu, C Zhang, F Wang 2016 IEEE International Conference on Healthcare Informatics (ICHI), 184-191, 2016 | 53 | 2016 |
Robust few-shot learning for user-provided data J Lu, S Jin, J Liang, C Zhang IEEE transactions on neural networks and learning systems 32 (4), 1433-1447, 2020 | 51 | 2020 |
Why attentions may not be interpretable? B Bai, J Liang, G Zhang, H Li, K Bai, F Wang Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data …, 2021 | 48 | 2021 |
Relation-guided representation learning Z Kang, X Lu, J Liang, K Bai, Z Xu Neural Networks 131, 93-102, 2020 | 44 | 2020 |
Hybrid differentially private federated learning on vertically partitioned data C Wang, J Liang, M Huang, B Bai, K Bai, H Li arXiv preprint arXiv:2009.02763, 2020 | 42 | 2020 |
Contrastive graph structure learning via information bottleneck for recommendation C Wei, J Liang, D Liu, F Wang Advances in Neural Information Processing Systems 35, 20407-20420, 2022 | 40 | 2022 |
Selection bias explorations and debias methods for natural language sentence matching datasets G Zhang, B Bai, J Liang, K Bai, S Chang, M Yu, C Zhu, T Zhao arXiv preprint arXiv:1905.06221, 2019 | 31 | 2019 |
General-purpose user embeddings based on mobile app usage J Zhang, B Bai, Y Lin, J Liang, K Bai, F Wang Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 30 | 2020 |
Pareto Domain Adaptation F Lv, J Liang, K Gong, S Li, C Liu, H Li, D Liu, G Wang Advances in Neural Information Processing Systems 34, 2021 | 29* | 2021 |
Two sides of the same coin: White-box and black-box attacks for transfer learning Y Zhang, Y Song, J Liang, K Bai, Q Yang Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 26 | 2020 |
Leveraging mixed and incomplete outcomes via reduced-rank modeling C Luo, J Liang, G Li, F Wang, C Zhang, DK Dey, K Chen Journal of Multivariate Analysis 167, 378-394, 2018 | 24 | 2018 |
Policy-driven attack: Learning to query for hard-label black-box adversarial examples Z Yan, Y Guo, J Liang, C Zhang International Conference on Learning Representations, 2021 | 20 | 2021 |