| CityFlow: A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario H Zhang, S Feng, C Liu, Y Ding, Y Zhu, Z Zhou, W Zhang, Y Yu, H Jin, Z Li The World Wide Web Conference, 3620-3624, 2019 | 304 | 2019 |
| Quality of information aware incentive mechanisms for mobile crowd sensing systems H Jin, L Su, D Chen, K Nahrstedt, J Xu Proceedings of the 16th ACM International Symposium on Mobile Ad Hoc …, 2015 | 300 | 2015 |
| Inception: Incentivizing privacy-preserving data aggregation for mobile crowd sensing systems H Jin, L Su, H Xiao, K Nahrstedt Proceedings of the 17th international symposium on mobile Ad Hoc networking …, 2016 | 202 | 2016 |
| Incentive mechanism for privacy-aware data aggregation in mobile crowd sensing systems H Jin, L Su, H Xiao, K Nahrstedt IEEE/ACM Transactions on Networking 26 (5), 2019-2032, 2018 | 158 | 2018 |
| Enabling privacy-preserving incentives for mobile crowd sensing systems H Jin, L Su, B Ding, K Nahrstedt, N Borisov 2016 IEEE 36th International Conference on Distributed Computing Systems …, 2016 | 156 | 2016 |
| Learning-aided computation offloading for trusted collaborative mobile edge computing Y Li, X Wang, X Gan, H Jin, L Fu, X Wang IEEE Transactions on Mobile Computing 19 (12), 2833-2849, 2019 | 151 | 2019 |
| Centurion: Incentivizing multi-requester mobile crowd sensing H Jin, L Su, K Nahrstedt INFOCOM 2017-IEEE Conference on Computer Communications, IEEE, 1-9, 2017 | 127 | 2017 |
| Spatiotemporal Adaptive Gated Graph Convolution Network for Urban Traffic Flow Forecasting B Lu, X Gan, H Jin, L Fu, H Zhang Proceedings of the 29th ACM International Conference on Information …, 2020 | 118 | 2020 |
| Theseus: Incentivizing truth discovery in mobile crowd sensing systems H Jin, L Su, K Nahrstedt Proceedings of the 18th ACM International Symposium on Mobile Ad Hoc …, 2017 | 94 | 2017 |
| MIRAS: Model-based Reinforcement Learning for Microservice Resource Allocation over Scientific Workflows Z Yang, P Nguyen, H Jin, K Nahrstedt 2019 IEEE 39th International Conference on Distributed Computing Systems …, 2019 | 93 | 2019 |
| Thanos: Incentive mechanism with quality awareness for mobile crowd sensing H Jin, L Su, D Chen, H Guo, K Nahrstedt, J Xu IEEE Transactions on Mobile Computing 18 (8), 1951-1964, 2018 | 81 | 2018 |
| Fast-Charging Station Deployment Considering Elastic Demand X Gan, H Zhang, G Hang, Z Qin, H Jin IEEE Transactions on Transportation Electrification 6 (1), 158-169, 2020 | 79 | 2020 |
| WritingHacker: audio based eavesdropping of handwriting via mobile devices T Yu, H Jin, K Nahrstedt Proceedings of the 2016 ACM International Joint Conference on Pervasive and …, 2016 | 73 | 2016 |
| Joint charging and relocation recommendation for e-taxi drivers via multi-agent mean field hierarchical reinforcement learning E Wang, R Ding, Z Yang, H Jin, C Miao, L Su, F Zhang, C Qiao, X Wang IEEE Transactions on Mobile Computing 21 (4), 1274-1290, 2020 | 51 | 2020 |
| Double Insurance: Incentivized Federated Learning with Differential Privacy in Mobile Crowdsensing C Ying, H Jin, X Wang, Y Luo 2020 International Symposium on Reliable Distributed Systems (SRDS), 81-90, 2020 | 45 | 2020 |
| Joint scheduling and incentive mechanism for spatio-temporal vehicular crowd sensing G Fan, H Jin, Q Liu, W Qin, X Gan, H Long, L Fu, X Wang IEEE Transactions on Mobile Computing 20 (4), 1449-1464, 2019 | 43 | 2019 |
| Dynamic Task Pricing in Multi-Requester Mobile Crowd Sensing with Markov Correlated Equilibrium H Jin, H Guo, L Su, K Nahrstedt, X Wang IEEE INFOCOM 2019-IEEE Conference on Computer Communications, 1063-1071, 2019 | 40 | 2019 |
| STP-TrellisNets: Spatial-Temporal Parallel TrellisNets for Metro Station Passenger Flow Prediction J Ou, J Sun, Y Zhu, H Jin, Y Liu, F Zhang, J Huang, X Wang Proceedings of the 29th ACM International Conference on Information …, 2020 | 37 | 2020 |
| Data-Driven Pricing for Sensing Effort Elicitation in Mobile Crowd Sensing Systems H Jin, B He, L Su, K Nahrstedt, X Wang IEEE/ACM Transactions on Networking 27 (6), 2208-2221, 2019 | 37 | 2019 |
| Data acquisition for real-time decision-making under freshness constraints S Hu, S Yao, H Jin, Y Zhao, Y Hu, X Liu, N Naghibolhosseini, S Li, ... 2015 IEEE Real-Time Systems Symposium, 185-194, 2015 | 36 | 2015 |
Klara NahrstedtComputer Science, University of Illinois, Urbana-ChampaignVerified email at illinois.edu
