| Diagnosing New York city's noises with ubiquitous data Y Zheng, T Liu, Y Wang, Y Zhu, Y Liu, E Chang Proceedings of the 2014 ACM international joint conference on pervasive and …, 2014 | 281 | 2014 |
| A mutually supervised graph attention network for few-shot segmentation: the perspective of fully utilizing limited samples H Gao, J Xiao, Y Yin, T Liu, J Shi IEEE Transactions on neural networks and learning systems, 2022 | 137 | 2022 |
| Digital-twin-assisted task offloading based on edge collaboration in the digital twin edge network T Liu, L Tang, W Wang, Q Chen, X Zeng IEEE Internet of Things Journal 9 (2), 1427-1444, 2021 | 105 | 2021 |
| Ppo2: Location privacy-oriented task offloading to edge computing using reinforcement learning for intelligent autonomous transport systems H Gao, W Huang, T Liu, Y Yin, Y Li IEEE transactions on intelligent transportation systems, 2022 | 74 | 2022 |
| Online computation offloading and resource scheduling in mobile-edge computing T Liu, Y Zhang, Y Zhu, W Tong, Y Yang IEEE Internet of Things Journal 8 (8), 6649-6664, 2021 | 56 | 2021 |
| Graph-enhanced spatial-temporal network for next POI recommendation Z Wang, Y Zhu, Q Zhang, H Liu, C Wang, T Liu ACM Transactions on Knowledge Discovery from Data (TKDD) 16 (6), 1-21, 2022 | 48 | 2022 |
| : When Active Learning Meets Compressive Crowdsensing for Urban Air Pollution Monitoring T Liu, Y Zhu, Y Yang, F Ye IEEE Internet of Things Journal 6 (6), 9427-9438, 2019 | 39 | 2019 |
| Resource allocation in dt-assisted internet of vehicles via edge intelligent cooperation T Liu, L Tang, W Wang, X He, Q Chen, X Zeng, H Jiang IEEE Internet of Things Journal 9 (18), 17608-17626, 2022 | 33 | 2022 |
| Predicting taxi demands via an attention-based convolutional recurrent neural network T Liu, W Wu, Y Zhu, W Tong Knowledge-Based Systems 206, 106294, 2020 | 32 | 2020 |
| Social welfare maximization in participatory smartphone sensing T Liu, Y Zhu Computer Networks 73, 195-209, 2014 | 30 | 2014 |
| Cgan-based collaborative intrusion detection for uav networks: A blockchain-empowered distributed federated learning approach X He, Q Chen, L Tang, W Wang, T Liu IEEE Internet of Things Journal 10 (1), 120-132, 2022 | 29 | 2022 |
| Deep reinforcement learning based approach for online service placement and computation resource allocation in edge computing T Liu, S Ni, X Li, Y Zhu, L Kong, Y Yang IEEE Transactions on Mobile Computing, 2022 | 26 | 2022 |
| A mixed transmission strategy to achieve energy balancing in wireless sensor networks T Liu, T Gu, N Jin, Y Zhu IEEE Transactions on wireless communications 16 (4), 2111-2122, 2017 | 26 | 2017 |
| Methods for sensing urban noises T Liu, Y Zheng, L Liu, Y Liu, Y Zhu Tec. Rep. MSR-TR-2014-66, 2014 | 26 | 2014 |
| Proximal policy optimization with mixed distributed training Z Zhang, X Luo, T Liu, S Xie, J Wang, W Wang, Y Li, Y Peng 2019 IEEE 31st international conference on tools with artificial …, 2019 | 25 | 2019 |
| A near-optimal approach for online task offloading and resource allocation in edge-cloud orchestrated computing T Liu, L Fang, Y Zhu, W Tong, Y Yang IEEE Transactions on Mobile Computing 21 (8), 2687-2700, 2020 | 22 | 2020 |
| A noise map of New York city Y Wang, Y Zheng, T Liu Proceedings of the 2014 ACM International Joint Conference on Pervasive and …, 2014 | 20 | 2014 |
| Stochastic optimal control for participatory sensing systems with heterogenous requests T Liu, Y Zhu, Q Zhang, A Vasilakos IEEE Transactions on Computers 65 (5), 1619-1631, 2015 | 19 | 2015 |
| Distributed social welfare maximization in urban vehicular participatory sensing systems T Liu, Y Zhu, R Jiang, Q Zhao IEEE Transactions on Mobile Computing 17 (6), 1314-1325, 2017 | 18 | 2017 |
| Incentive design for air pollution monitoring based on compressive crowdsensing T Liu, Y Zhu, Y Yang, F Ye 2016 IEEE Global Communications Conference (GLOBECOM), 1-6, 2016 | 18 | 2016 |
