| Adaptive hash retrieval with kernel based similarity X Bai, C Yan, H Yang, L Bai, J Zhou, ER Hancock Pattern Recognition 75, 136-148, 2018 | 44 | 2018 |
| Data-dependent hashing based on p-stable distribution X Bai, H Yang, J Zhou, P Ren, J Cheng IEEE Transactions on Image Processing 23 (12), 5033-5046, 2014 | 40 | 2014 |
| Model compression with adversarial robustness: A unified optimization framework S Gui, H Wang, C Yu, H Yang, Z Wang, J Liu arXiv preprint arXiv:1902.03538, 2019 | 34* | 2019 |
| Energy-constrained compression for deep neural networks via weighted sparse projection and layer input masking H Yang, Y Zhu, J Liu arXiv preprint arXiv:1806.04321, 2018 | 24* | 2018 |
| Ecc: Platform-independent energy-constrained deep neural network compression via a bilinear regression model H Yang, Y Zhu, J Liu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 22 | 2019 |
| Adaptive object retrieval with kernel reconstructive hashing H Yang, X Bai, J Zhou, P Ren, Z Zhang, J Cheng Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2014 | 18 | 2014 |
| Online feature selection: A limited-memory substitution algorithm and its asynchronous parallel variation H Yang, R Fujimaki, Y Kusumura, J Liu Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge …, 2016 | 16 | 2016 |
| A robust AUC maximization framework with simultaneous outlier detection and feature selection for positive-unlabeled classification K Ren, H Yang, Y Zhao, W Chen, M Xue, H Miao, S Huang, J Liu IEEE transactions on neural networks and learning systems 30 (10), 3072-3083, 2018 | 9 | 2018 |
| Marginal policy gradients: A unified family of estimators for bounded action spaces with applications C Eisenach, H Yang, J Liu, H Liu arXiv preprint arXiv:1806.05134, 2018 | 8* | 2018 |
| Learning simple thresholded features with sparse support recovery H Xu, Z Wang, H Yang, D Liu, J Liu IEEE Transactions on Circuits and Systems for Video Technology 30 (4), 970-982, 2019 | 7* | 2019 |
| Maximum margin hashing with supervised information H Yang, X Bai, Y Liu, Y Wang, L Bai, J Zhou, W Tang Multimedia Tools and Applications 75 (7), 3955-3971, 2016 | 7 | 2016 |
| On benefits of selection diversity via bilevel exclusive sparsity H Yang, Y Huang, L Tran, J Liu, S Huang Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 7 | 2016 |
| Automatic neural network compression by sparsity-quantization joint learning: A constrained optimization-based approach H Yang, S Gui, Y Zhu, J Liu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 6 | 2020 |
| GAN Slimming: All-in-One GAN Compression by A Unified Optimization Framework H Wang, S Gui, H Yang, J Liu, Z Wang European Conference on Computer Vision, 54-73, 2020 | 2 | 2020 |
| Learning graph model for different dimensions image matching H Zhou, X Bai, J Zhou, H Yang, Y Liu International Workshop on Graph-Based Representations in Pattern Recognition …, 2015 | 2 | 2015 |
| Label propagation hashing based on p-stable distribution and coordinate descent H Yang, X Bai, C Liu, J Zhou 2013 IEEE International Conference on Image Processing, 2674-2678, 2013 | 2 | 2013 |
| Autonomic flexibility reflects learning and associated neuroplasticity in old age Q Chen, H Yang, B Rooks, M Anthony, Z Zhang, D Tadin, KL Heffner, ... Human brain mapping 41 (13), 3608-3619, 2020 | 1 | 2020 |
| PARAMETRIZED DEEP Q-NETWORKS LEARNING: PLAYING ONLINE BATTLE ARENA WITH DISCRETE-CONTINUOUS HYBRID ACTION SPACE J Xiong, Q Wang, Z Yang, P Sun, Y Zheng, L Han, H Fu, X Lian, ... | 1 | 2018 |
| Sparse learning for model optimization H Yang | | 2020 |
| A Large Margin Learning Method for Matching Images of Natural Objects with Different Dimensions H Zhou, J Zhou, H Yang, C Yan, X Bai, Y Liu Geospatial Intelligence: Concepts, Methodologies, Tools, and Applications …, 2019 | | 2019 |
