| Spatiotemporal modeling and prediction in cellular networks: A big data enabled deep learning approach J Wang, J Tang, Z Xu, Y Wang, G Xue, X Zhang, D Yang IEEE INFOCOM 2017-IEEE Conference on Computer Communications, 1-9, 2017 | 145 | 2017 |
| Experience-driven networking: A deep reinforcement learning based approach Z Xu, J Tang, J Meng, W Zhang, Y Wang, CH Liu, D Yang IEEE INFOCOM 2018-IEEE Conference on Computer Communications, 1871-1879, 2018 | 143 | 2018 |
| A deep reinforcement learning based framework for power-efficient resource allocation in cloud RANs Z Xu, Y Wang, J Tang, J Wang, MC Gursoy 2017 IEEE International Conference on Communications (ICC), 1-6, 2017 | 138 | 2017 |
| A hierarchical framework of cloud resource allocation and power management using deep reinforcement learning N Liu, Z Li, J Xu, Z Xu, S Lin, Q Qiu, J Tang, Y Wang 2017 IEEE 37th International Conference on Distributed Computing Systems …, 2017 | 114 | 2017 |
| Learning-based energy-efficient data collection by unmanned vehicles in smart cities B Zhang, CH Liu, J Tang, Z Xu, J Ma, W Wang IEEE Transactions on Industrial Informatics 14 (4), 1666-1676, 2017 | 62 | 2017 |
| Model-free control for distributed stream data processing using deep reinforcement learning T Li, Z Xu, J Tang, Y Wang arXiv preprint arXiv:1803.01016, 2018 | 47 | 2018 |
| Deep reinforcement learning for dynamic treatment regimes on medical registry data Y Liu, B Logan, N Liu, Z Xu, J Tang, Y Wang 2017 IEEE International Conference on Healthcare Informatics (ICHI), 380-385, 2017 | 47 | 2017 |
| Experience-driven congestion control: When multi-path TCP meets deep reinforcement learning Z Xu, J Tang, C Yin, Y Wang, G Xue IEEE Journal on Selected Areas in Communications 37 (6), 1325-1336, 2019 | 45 | 2019 |
| AutoCompress: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates. N Liu, X Ma, Z Xu, Y Wang, J Tang, J Ye AAAI, 4876-4883, 2020 | 22 | 2020 |
| Adversarial meta-learning C Yin, J Tang, Z Xu, Y Wang arXiv preprint arXiv:1806.03316, 2018 | 13 | 2018 |
| Learning the dynamic treatment regimes from medical registry data through deep q-network N Liu, Y Liu, B Logan, Z Xu, J Tang, Y Wang Scientific reports 9 (1), 1-10, 2019 | 5 | 2019 |
| AutoSlim: An automatic DNN structured pruning framework for ultra-high compression rates N Liu, X Ma, Z Xu, Y Wang, J Tang, J Ye arXiv preprint arXiv:1907.03141, 2019 | 3 | 2019 |
| Memory augmented deep recurrent neural network for video question answering C Yin, J Tang, Z Xu, Y Wang IEEE transactions on neural networks and learning systems, 2019 | 2 | 2019 |
| Knowledge Transfer in Multi-Task Deep Reinforcement Learning for Continuous Control Z Xu, K Wu, Z Che, J Tang, J Ye | | 2020 |
| A Deep Recurrent Neural Network Based Predictive Control Framework for Reliable Distributed Stream Data Processing J Xu, J Tang, Z Xu, C Yin, K Kwiat, C Kamhoua 2019 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2019 | | 2019 |
Jian TangProfessor, IEEE Fellow and ACM Distinguished Member, Department of EECS, Syracuse UniversityDirección de correo verificada de syr.edu
