Connecting the dots: Multivariate time series forecasting with graph neural networks Z Wu, S Pan, G Long, J Jiang, X Chang, C Zhang Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 1534 | 2020 |
A survey of deep active learning P Ren, Y Xiao, X Chang, PY Huang, Z Li, BB Gupta, X Chen, X Wang ACM computing surveys (CSUR) 54 (9), 1-40, 2021 | 1337 | 2021 |
A Comprehensive Survey of Neural Architecture Search: Challenges and Solutions P Ren, Y Xiao, X Chang, PY Huang, Z Li, X Chen, X Wang ACM Computing Surveys 54 (4), 1-34, 2021 | 742 | 2021 |
Multi-class active learning by uncertainty sampling with diversity maximization Y Yang, Z Ma, F Nie, X Chang, AG Hauptmann International Journal of Computer Vision 113, 113-127, 2015 | 540 | 2015 |
Hierarchical neural architecture search for deep stereo matching X Cheng, Y Zhong, M Harandi, Y Dai, X Chang, H Li, T Drummond, Z Ge Advances in neural information processing systems 33, 22158-22169, 2020 | 379 | 2020 |
A semisupervised recurrent convolutional attention model for human activity recognition K Chen, L Yao, D Zhang, X Wang, X Chang, F Nie IEEE transactions on neural networks and learning systems 31 (5), 1747-1756, 2019 | 366 | 2019 |
Semantic pooling for complex event analysis in untrimmed videos X Chang, YL Yu, Y Yang, EP Xing IEEE transactions on pattern analysis and machine intelligence 39 (8), 1617-1632, 2017 | 353 | 2017 |
Making sense of spatio-temporal preserving representations for EEG-based human intention recognition D Zhang, L Yao, K Chen, S Wang, X Chang, Y Liu IEEE transactions on cybernetics 50 (7), 3033-3044, 2019 | 342 | 2019 |
A comprehensive survey of scene graphs: Generation and application X Chang, P Ren, P Xu, Z Li, X Chen, A Hauptmann IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (1), 1-26, 2021 | 335 | 2021 |
An adaptive semisupervised feature analysis for video semantic recognition M Luo, X Chang, L Nie, Y Yang, AG Hauptmann, Q Zheng IEEE transactions on cybernetics 48 (2), 648-660, 2017 | 328 | 2017 |
A convex formulation for semi-supervised multi-label feature selection X Chang, F Nie, Y Yang, H Huang Proceedings of the AAAI conference on artificial intelligence 28 (1), 2014 | 293 | 2014 |
Rank-constrained spectral clustering with flexible embedding Z Li, F Nie, X Chang, L Nie, H Zhang, Y Yang IEEE transactions on neural networks and learning systems 29 (12), 6073-6082, 2018 | 272 | 2018 |
Dynamic affinity graph construction for spectral clustering using multiple features Z Li, F Nie, X Chang, Y Yang, C Zhang, N Sebe IEEE transactions on neural networks and learning systems 29 (12), 6323-6332, 2018 | 270 | 2018 |
Vision-language navigation with self-supervised auxiliary reasoning tasks F Zhu, Y Zhu, X Chang, X Liang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 266 | 2020 |
Self-supervised deep correlation tracking D Yuan, X Chang, PY Huang, Q Liu, Z He IEEE Transactions on Image Processing 30, 976-985, 2020 | 262 | 2020 |
Bi-level semantic representation analysis for multimedia event detection X Chang, Z Ma, Y Yang, Z Zeng, AG Hauptmann IEEE transactions on cybernetics 47 (5), 1180-1197, 2016 | 246 | 2016 |
Semisupervised feature analysis by mining correlations among multiple tasks X Chang, Y Yang IEEE transactions on neural networks and learning systems 28 (10), 2294-2305, 2016 | 245 | 2016 |
Adaptive unsupervised feature selection with structure regularization M Luo, F Nie, X Chang, Y Yang, AG Hauptmann, Q Zheng IEEE transactions on neural networks and learning systems 29 (4), 944-956, 2017 | 240 | 2017 |
MMALFM: Explainable recommendation by leveraging reviews and images Z Cheng, X Chang, L Zhu, RC Kanjirathinkal, M Kankanhalli ACM Transactions on Information Systems (TOIS) 37 (2), 1-28, 2019 | 238 | 2019 |
Block-wisely supervised neural architecture search with knowledge distillation C Li, J Peng, L Yuan, G Wang, X Liang, L Lin, X Chang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 232 | 2020 |