| Crowdsourcing to smartphones: Incentive mechanism design for mobile phone sensing D Yang, G Xue, X Fang, J Tang ACM MobiCom 2012: Proceedings of the 18th annual international conference on …, 2012 | 1246 | 2012 |
| Interference-aware topology control and QoS routing in multi-channel wireless mesh networks J Tang, G Xue, W Zhang ACM MobiHoc 2005: Proceedings of the 6th ACM international symposium on …, 2005 | 672 | 2005 |
| Energy-efficient UAV control for effective and fair communication coverage: A deep reinforcement learning approach CH Liu, Z Chen, J Tang, J Xu, C Piao IEEE Journal on Selected Areas in Communications 36 (9), 2059-2070, 2018 | 616 | 2018 |
| A systematic dnn weight pruning framework using alternating direction method of multipliers T Zhang, S Ye, K Zhang, J Tang, W Wen, M Fardad, Y Wang Proceedings of the European conference on computer vision (ECCV), 184-199, 2018 | 560 | 2018 |
| 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 | 483 | 2018 |
| Incentive mechanisms for crowdsensing: Crowdsourcing with smartphones D Yang, G Xue, X Fang, J Tang IEEE/ACM transactions on networking 24 (3), 1732-1744, 2015 | 483 | 2015 |
| Relay node placement in large scale wireless sensor networks J Tang, B Hao, A Sen Computer Communications Journal 29 (4), 490-501, 2006 | 456 | 2006 |
| 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 | 453 | 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 | 345 | 2017 |
| C ir CNN: accelerating and compressing deep neural networks using block-circulant weight matrices C Ding, S Liao, Y Wang, Z Li, N Liu, Y Zhuo, C Wang, X Qian, Y Bai, ... IEEE/ACM MICRO 2017: Proceedings of the 50th Annual IEEE/ACM International …, 2017 | 343 | 2017 |
| 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 | 321 | 2017 |
| Optimizing electric vehicle charging: A customer's perspective C Jin, J Tang, P Ghosh IEEE Transactions on vehicular technology 62 (7), 2919-2927, 2013 | 318 | 2013 |
| Optimizing electric vehicle charging with energy storage in the electricity market C Jin, J Tang, P Ghosh IEEE Transactions on Smart Grid 4 (1), 311-320, 2013 | 299 | 2013 |
| T-storm: Traffic-aware online scheduling in storm J Xu, Z Chen, J Tang, S Su IEEE ICDCS 2014: 34th IEEE International Conference on Distributed Computing …, 2014 | 283 | 2014 |
| Distributed energy-efficient multi-UAV navigation for long-term communication coverage by deep reinforcement learning CH Liu, X Ma, X Gao, J Tang IEEE Transactions on Mobile Computing 19 (6), 1274-1285, 2019 | 256 | 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 Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 4876-4883, 2020 | 237 | 2020 |
| Sensing as a service: Challenges, solutions and future directions X Sheng, J Tang, X Xiao, G Xue IEEE Sensors Journal 13 (10), 3733-3741, 2013 | 236 | 2013 |
| Learning gradient fields for molecular conformation generation C Shi, S Luo, M Xu, J Tang International conference on machine learning, 9558-9568, 2021 | 234 | 2021 |
| Constrained relay node placement in wireless sensor networks: Formulation and approximations S Misra, SD Hong, G Xue, J Tang IEEE/ACM Transactions on networking 18 (2), 434-447, 2009 | 222 | 2009 |
| Pconv: The missing but desirable sparsity in dnn weight pruning for real-time execution on mobile devices X Ma, FM Guo, W Niu, X Lin, J Tang, K Ma, B Ren, Y Wang Proceedings of the AAAI conference on artificial intelligence 34 (04), 5117-5124, 2020 | 213 | 2020 |
Guoliang XueProfessor of Computer Science and Engineering, Arizona State UniversityVerified email at asu.edu
