| Semantic Amodal Segmentation Y Zhu, Y Tian, D Metaxas, P Dollár Computer Vision and Pattern Recognition (CVPR), 2017, 2015 | 183 | 2015 |
| Better Computer Go Player with Neural Network and Long-term Prediction Y Tian, Y Zhu International Conference on Learning Representation (ICLR) 2016, 2015 | 130 | 2015 |
| Sparse coding on local spatial-temporal volumes for human action recognition Y Zhu, X Zhao, Y Fu, Y Liu Computer Vision–ACCV 2010: 10th Asian Conference on Computer Vision …, 2011 | 108 | 2011 |
| Explainable Fairness in Recommendation Y Ge, J Tan, Y Zhu, Y Xia, J Luo, S Liu, Z Fu, S Geng, Z Li, Y Zhang SIGIR 2022, 2022 | 57 | 2022 |
| RawlsGCN: Towards Rawlsian Difference Principle on Graph Convolutional Network J Kang, Y Zhu, Y Xia, J Luo, H Tong Proceedings of the ACM Web Conference 2022, 1214-1225, 2022 | 55 | 2022 |
| Computing the M most probable modes of a graphical model C Chen, V Kolmogorov, Y Zhu, D Metaxas, C Lampert Artificial Intelligence and Statistics, 161-169, 2013 | 42 | 2013 |
| What is new in our city? a framework for event extraction using social media posts C Xia, J Hu, Y Zhu, M Naaman Advances in Knowledge Discovery and Data Mining: 19th Pacific-Asia …, 2015 | 28 | 2015 |
| Scalable histopathological image analysis via active learning Y Zhu, S Zhang, W Liu, DN Metaxas International Conference on Medical Image Computing and Computer-Assisted …, 2014 | 25 | 2014 |
| Video classification via weakly supervised sequence modeling J Liu, C Chen, Y Zhu, W Liu, DN Metaxas Computer Vision and Image Understanding 152, 79-87, 2016 | 18 | 2016 |
| Batch Active Learning with Graph Neural Networks via Multi-Agent Deep Reinforcement Learning Y Zhang, H Tong, Y Xia, Y Zhu, Y Chi, L Ying AAAI 2022, 2022 | 15 | 2022 |
| Rethinking Incentives in Recommender Systems: Are Monotone Rewards Always Beneficial? HX Fan Yao, Chuanhao Li, Karthik Abinav Sankararaman, Yiming Liao, Yan Zhu ... Advances in Neural Information Processing Systems 36, 2024 | 11 | 2024 |
| Time-based Sequence Model for Personalization and Recommendation Systems T Ishkhanov, M Naumov, X Chen, Y Zhu, Y Zhong, AG Azzolini, C Sun, ... arXiv preprint arXiv:2008.11922, 2020 | 11 | 2020 |
| Interactive Reinforcement Learning for Object Grounding via Self-Talking Y Zhu, S Zhang, D Metaxas Neural Information Processing Systems 2017 - VIGIL workshop, 2017 | 9 | 2017 |
| Efficient Dynamic Graph Representation Learning at Scale X Chen, Y Zhu, H Xu, M Liu, L Xiong, M Zhang, L Song arXiv preprint arXiv:2112.07768, 2021 | 7 | 2021 |
| User-Controllable Recommendation via Counterfactual Retrospective and Prospective Explanations J Tan, Y Ge, Y Zhu, Y Xia, J Luo, J Ji, Y Zhang arXiv preprint arXiv:2308.00894, 2023 | 2 | 2023 |
| User Welfare Optimization in Recommender Systems with Competing Content Creators F Yao, Y Liao, M Wu, C Li, Y Zhu, J Yang, Q Wang, H Xu, H Wang arXiv preprint arXiv:2404.18319, 2024 | 1 | 2024 |
| Active Heterogeneous Graph Neural Networks with Per-step Meta-Q-Learning Y Zhang, Y Xia, Y Zhu, Y Chi, L Ying, H Tong 2022 IEEE International Conference on Data Mining (ICDM), 1329-1334, 2022 | 1 | 2022 |
| Representation Learning on Dynamic Network of Networks S Zhang, Y Xia, Y Zhu, H Tong Proceedings of the 2023 SIAM International Conference on Data Mining (SDM …, 2023 | | 2023 |
| Flexible multi-task neutral network for content ranking L Xiong, Y Zhu US Patent 11,017,287, 2021 | | 2021 |
Dimitris N. MetaxasBoard of Governors Professor of Computer Science, Rutgers UniversityVerified email at cs.rutgers.edu
