| Learning with Structured Sparsity. J Huang, T Zhang, D Metaxas Journal of Machine Learning Research 12 (11), 2011 | 634 | 2011 |
| Robust tracking using local sparse appearance model and k-selection B Liu, J Huang, L Yang, C Kulikowsk CVPR 2011, 1313-1320, 2011 | 581 | 2011 |
| Dropedge: Towards deep graph convolutional networks on node classification Y Rong, W Huang, T Xu, J Huang ICLR 2020 (arXiv preprint arXiv:1907.10903), 2019 | 518 | 2019 |
| The benefit of group sparsity J Huang, T Zhang The Annals of Statistics 38 (4), 1978-2004, 2010 | 514 | 2010 |
| Discrimination-aware channel pruning for deep neural networks Z Zhuang, M Tan, B Zhuang, J Liu, Y Guo, Q Wu, J Huang, J Zhu NeurIPS 2018 (arXiv preprint arXiv:1810.11809), 2018 | 484 | 2018 |
| Adaptive graph convolutional neural networks R Li, S Wang, F Zhu, J Huang Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 434 | 2018 |
| Learning active facial patches for expression analysis L Zhong, Q Liu, P Yang, B Liu, J Huang, DN Metaxas 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2562-2569, 2012 | 394 | 2012 |
| Large-scale multi-view spectral clustering via bipartite graph Y Li, F Nie, H Huang, J Huang Twenty-ninth AAAI conference on artificial intelligence, 2015 | 351 | 2015 |
| Efficient MR image reconstruction for compressed MR imaging J Huang, S Zhang, D Metaxas Medical Image Analysis 15 (5), 670-679, 2011 | 339 | 2011 |
| Pose-free facial landmark fitting via optimized part mixtures and cascaded deformable shape model X Yu, J Huang, S Zhang, W Yan, DN Metaxas Proceedings of the IEEE international conference on computer vision, 1944-1951, 2013 | 308 | 2013 |
| Adaptive sampling towards fast graph representation learning W Huang, T Zhang, Y Rong, J Huang NeurIPS 2018 (arXiv preprint arXiv:1809.05343), 2018 | 303 | 2018 |
| Towards robust and effective shape modeling: Sparse shape composition S Zhang, Y Zhan, M Dewan, J Huang, DN Metaxas, XS Zhou Medical image analysis 16 (1), 265-277, 2012 | 291 | 2012 |
| Graph convolutional networks for temporal action localization R Zeng, W Huang, M Tan, Y Rong, P Zhao, J Huang, C Gan Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 272 | 2019 |
| Robust and fast collaborative tracking with two stage sparse optimization B Liu, L Yang, J Huang, P Meer, L Gong, C Kulikowski European conference on computer vision, 624-637, 2010 | 272 | 2010 |
| Automatic image annotation using group sparsity S Zhang, J Huang, Y Huang, Y Yu, H Li, DN Metaxas 2010 IEEE Computer Society Conference on Computer Vision and Pattern …, 2010 | 236 | 2010 |
| Progressive feature alignment for unsupervised domain adaptation C Chen, W Xie, W Huang, Y Rong, X Ding, Y Huang, T Xu, J Huang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 230 | 2019 |
| A new iris segmentation method for recognition J Huang, Y Wang, T Tan, J Cui Proceedings of the 17th International Conference on Pattern Recognition …, 2004 | 196 | 2004 |
| Learning with dynamic group sparsity J Huang, X Huang, D Metaxas 2009 IEEE 12th International Conference on Computer Vision, 64-71, 2009 | 195 | 2009 |
| Early triage of critically ill COVID-19 patients using deep learning W Liang, J Yao, A Chen, Q Lv, M Zanin, J Liu, SS Wong, Y Li, J Lu, ... Nature communications 11 (1), 1-7, 2020 | 188 | 2020 |
| End-to-end learning of motion representation for video understanding L Fan, W Huang, C Gan, S Ermon, B Gong, J Huang Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 179 | 2018 |
Dimitris N. MetaxasDistinguished Professor of Computer Science, Rutgers UniversityVerified email at cs.rutgers.edu
