| Multi-Task Allocation in Mobile Crowd Sensing with Individual Task Quality Assurance Jiangtao Wang, Yasha Wang, Daqing Zhang, Feng Wang, Haoyi Xiong,Chao Chen ... IEEE Transactions on Mobile Computing 17 (9), 2101-2113, 2018 | 122 | 2018 |
| Task Allocation in Mobile Crowd Sensing: State of the Art and Future Opportunities Jiangtao Wang, Leye Wang, Yasha Wang, Daqing Zhang, Linghe Kong IEEE Internet of Things Journal 5 (5), 3747-3757, 2018 | 97 | 2018 |
| HyTasker: Hybrid Task Allocation in Mobile Crowd Sensing Jiangtao Wang, Feng Wang, Yasha Wang, Leye Wang, zhaopeng Qiu, Daqing Zhang ... IEEE Transactions on Mobile Computing, 2020 | 89* | 2020 |
| Social-Network-Assisted Worker Recruitment in Mobile Crowd Sensing Jiangtao Wang, Feng Wang, Yasha Wang, Daqing Zhang, Leye Wang, Zhaopeng Qiu IEEE Transactions on Mobile Computing 18 (7), 1661 - 1673, 2019 | 80* | 2019 |
| PSAllocator: Multi-task Allocation for Participatory Sensing with Sensing Capability Constraints Jiangtao Wang, Yasha Wang, Daqing Zhang, Feng Wang, Yuanduo He, Liantao Ma Proceedings of the 2017 ACM Conference on Computer Supported Cooperative …, 2017 | 76 | 2017 |
| ConCare: Personalized Clinical Feature Embedding via Capturing the Healthcare Context L Ma, C Zhang, Y Wang, W Ruan, J Wang, W Tang, X Ma, X Gao, J Gao AAAI 2020, 2020 | 62 | 2020 |
| Fine-grained Multitask Allocation for Participatory Sensing with a Shared Budget J Wang, Y Wang, D Zhang, L Wang, H Xiong, A Helal, Y He, F Wang IEEE Internet of Things Journal 3 (6), 1395-1405, 2016 | 60 | 2016 |
| AdaCare: Explainable Clinical Health Status Representation Learning via Scale-Adaptive Feature Extraction and Recalibration L Ma, J Gao, Y Wang, C Zhang, J Wang, W Ruan, W Tang, X Gao, X Ma AAAI 2020, 2020 | 53 | 2020 |
| Energy Saving Techniques in Mobile Crowd Sensing: Current State and Future Opportunities Jiangtao Wang, Yasha Wang, Daqing Zhang, Sumi Helal IEEE Communications Magazine 56 (5), 164-169, 2018 | 50 | 2018 |
| Camp: Co-attention memory networks for diagnosis prediction in healthcare J Gao, X Wang, Y Wang, Z Yang, J Gao, J Wang, W Tang, X Xie IEEE International Conference on Data Mining (ICDM 2019) 10361041, 2019 | 45 | 2019 |
| Green, Pervasive, and Cloud Computing–GPC 2020 Workshops: 15th International Conference, GPC 2020, Xi'an, China, November 13–15, 2020, Proceedings J Wang, L Chen, L Tang, Y Liang Springer Nature, 2020 | 39 | 2020 |
| Learning-Assisted Optimization in Mobile Crowd Sensing: A Survey Jiangtao Wang, Yasha Wang, Daqing Zhang, Jorge Goncalves, Denzil Ferreira ... IEEE Transactions on Industrial Informatics 15 (1), 15-22, 2019 | 39* | 2019 |
| Real-time and generic queue time estimation based on mobile crowdsensing Jiangtao Wang, Yasha Wang, Daqing Zhang,Leye Wang,Chao Chen, Jae Woong Lee ... Frontiers of computer Science 11 (1), 49-60, 2017 | 39 | 2017 |
| Allocating Heterogeneous Tasks in Participatory Sensing with Diverse Participant-Side Factors J Wang, F Wang, Y Wang, D Zhang, BY Lim, L Wang IEEE Transactions on Mobile Computing 18 (9), 1979 - 1991, 2019 | 34 | 2019 |
| Crowd-Powered Sensing and Actuation in Smart Cities: Current Issues and Future Directions J Wang, Y Wang, D Zhang, Q Lv, C Chen IEEE Wireless Communications 26 (2), 86-92, 2019 | 31 | 2019 |
| A survey of task allocation: contrastive perspectives from wireless sensor networks and mobile crowdsensing W Guo, W Zhu, Z Yu, J Wang, B Guo IEEE Access 7, 78406-78420, 2019 | 31 | 2019 |
| Mlrda: A multi-task semi-supervised learning framework for drug-drug interaction prediction X Chu, Y Lin, Y Wang, L Wang, J Wang, J Gao Proceedings of the 28th International Joint Conference on Artificial …, 2019 | 30 | 2019 |
| Qtime: A queuing-time notification system based on participatory sensing data Y Wang, J Wang, X Zhang Computer Software and Applications Conference (COMPSAC), 2013 IEEE 37th …, 2013 | 22 | 2013 |
| Swarm-intelligence-based rendezvous selection via edge computing for mobile sensor networks X Liu, T Qiu, B Dai, L Yang, A Liu, J Wang IEEE Internet of Things Journal 7 (10), 9471-9480, 2020 | 19 | 2020 |
| Interpretable machine learning for covid-19: an empirical study on severity prediction task H Wu, W Ruan, J Wang, D Zheng, B Liu, Y Geng, X Chai, J Chen, K Li, ... IEEE Transactions on Artificial Intelligence, 2021 | 18* | 2021 |
Daqing Zhang, IEEE FellowChair Professor, Telecom SudParis/Peking UniversityVerified email at telecom-sudparis.eu
