Clustering and projected clustering with adaptive neighbors F Nie, X Wang, H Huang Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014 | 908 | 2014 |
The constrained laplacian rank algorithm for graph-based clustering F Nie, X Wang, M Jordan, H Huang Proceedings of the AAAI conference on artificial intelligence 30 (1), 2016 | 783 | 2016 |
Learning a structured optimal bipartite graph for co-clustering F Nie, X Wang, C Deng, H Huang Advances in Neural Information Processing Systems 30, 2017 | 143 | 2017 |
Balanced self-paced learning for generative adversarial clustering network K Ghasedi, X Wang, C Deng, H Huang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 109 | 2019 |
New primal SVM solver with linear computational cost for big data classifications F Nie, Y Huang, X Wang, H Huang Proceedings of the 31st International Conference on International Conference …, 2014 | 85* | 2014 |
Multiclass capped ℓp-Norm SVM for robust classifications F Nie, X Wang, H Huang Proceedings of the aaai conference on artificial intelligence 31 (1), 2017 | 80 | 2017 |
Conditional generative adversarial network for gene expression inference X Wang, K Ghasedi Dizaji, H Huang Bioinformatics 34 (17), i603-i611, 2018 | 59 | 2018 |
Structured doubly stochastic matrix for graph based clustering: Structured doubly stochastic matrix X Wang, F Nie, H Huang Proceedings of the 22nd ACM SIGKDD International conference on Knowledge …, 2016 | 55 | 2016 |
Semi-supervised generative adversarial network for gene expression inference K Ghasedi Dizaji, X Wang, H Huang Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018 | 53 | 2018 |
Discriminative unsupervised dimensionality reduction X Wang, Y Liu, F Nie, H Huang Twenty-fourth international joint conference on artificial intelligence, 2015 | 49 | 2015 |
Shapley explanation networks R Wang, X Wang, DI Inouye arXiv preprint arXiv:2104.02297, 2021 | 44 | 2021 |
Regularized modal regression with applications in cognitive impairment prediction X Wang, H Chen, W Cai, D Shen, H Huang Advances in neural information processing systems 30, 2017 | 39* | 2017 |
Constructing a fair classifier with generated fair data T Jang, F Zheng, X Wang Proceedings of the AAAI Conference on Artificial Intelligence 35 (9), 7908-7916, 2021 | 34 | 2021 |
Group sparse additive machine H Chen, X Wang, C Deng, H Huang Advances in Neural Information Processing Systems 30, 2017 | 33 | 2017 |
Fairness with adaptive weights J Chai, X Wang International Conference on Machine Learning, 2853-2866, 2022 | 31 | 2022 |
Cognitive assessment prediction in Alzheimer’s disease by multi-layer multi-target regression X Wang, X Zhen, Q Li, D Shen, H Huang Neuroinformatics 16, 285-294, 2018 | 30 | 2018 |
Group-aware threshold adaptation for fair classification T Jang, P Shi, X Wang Proceedings of the AAAI Conference on Artificial Intelligence 36 (6), 6988-6995, 2022 | 29 | 2022 |
Fairness without demographics through knowledge distillation J Chai, T Jang, X Wang Advances in Neural Information Processing Systems 35, 19152-19164, 2022 | 28 | 2022 |
Prediction of memory impairment with MRI Data: a longitudinal study of Alzheimer’s disease X Wang, D Shen, H Huang Medical Image Computing and Computer-Assisted Intervention–MICCAI 2016: 19th …, 2016 | 25 | 2016 |
Self-supervised fair representation learning without demographics J Chai, X Wang Advances in Neural Information Processing Systems 35, 27100-27113, 2022 | 22 | 2022 |