Matching theory based low-latency scheme for multi-task federated learning in mec networks D Chen, CS Hong, L Wang, Y Zha, Y Zhang, X Liu, Z Han IEEE Internet of Things Journal 8 (14), 11415-11426, 2021 | 82 | 2021 |
Federated learning based mobile edge computing for augmented reality applications D Chen, LJ Xie, BG Kim, L Wang, CS Hong, LC Wang, Z Han 2020 international conference on computing, networking and communications …, 2020 | 78 | 2020 |
Edge computing resources reservation in vehicular networks: A meta-learning approach D Chen, YC Liu, BG Kim, J Xie, CS Hong, Z Han IEEE Transactions on Vehicular Technology 69 (5), 5634-5646, 2020 | 68 | 2020 |
Digital twin for federated analytics using a Bayesian approach D Chen, D Wang, Y Zhu, Z Han IEEE Internet of Things Journal 8 (22), 16301-16312, 2021 | 47 | 2021 |
Prediction of cloud resources demand based on hierarchical pythagorean fuzzy deep neural network D Chen, X Zhang, LL Wang, Z Han IEEE Transactions on Services Computing 14 (6), 1890 - 1901, 2019 | 32 | 2019 |
Metamobility: Connecting future mobility with the metaverse H Wang, Z Wang, D Chen, Q Liu, H Ke, KKT Han IEEE Vehicular Technology Magazine 18 (3), 69-79, 2023 | 24 | 2023 |
FedSVRG Based Communication Efficient Scheme for Federated Learning in MEC Networks D Chen, CS Hong, Y Zha, Y Zhang, X Liu, Z Han IEEE Transactions on Vehicular Technology 70 (7), 7300-7304, 2021 | 20 | 2021 |
Federated Learning for Wireless Networks CS Hong, LU Khan, M Chen, D Chen, W Saad, Z Han Springer Nature, 2021 | 14 | 2021 |
Deep reinforcement learning based strategy for quadrotor UAV pursuer and evader problem D Chen, Y Wei, L Wang, CS Hong, LC Wang, Z Han 2020 IEEE International Conference on Communications Workshops (ICC …, 2020 | 11 | 2020 |
Incentive framework for cross-device federated learning and analytics with multiple tasks based on a multi-leader-follower game Y Yu, D Chen, X Tang, T Song, CS Hong, Z Han IEEE Transactions on Network Science and Engineering 9 (5), 3749-3761, 2022 | 10 | 2022 |
Unveiling energy efficiency in deep learning: Measurement, prediction, and scoring across edge devices X Tu, A Mallik, D Chen, K Han, O Altintas, H Wang, J Xie 2023 IEEE/ACM Symposium on Edge Computing (SEC), 80-93, 2023 | 8 | 2023 |
Visualization of Mobility Digital Twin: Framework Design, Case Study, and Future Challenges Y Liu, X Tu, D Chen, K Han, O Altintas, H Wang, J Xie 2023 IEEE 20th International Conference on Mobile Ad Hoc and Smart Systems …, 2023 | 8 | 2023 |
Prediction of cloud resources demand based on fuzzy deep neural network D Chen, X Zhang, L Wang, Z Han 2018 IEEE Global Communications Conference (GLOBECOM), 1-5, 2018 | 8 | 2018 |
Methods and systems for selecting machine learning models to predict distributed computing resources D Chen, YC Liu, BG Kim US Patent App. 16/710,590, 2021 | 6 | 2021 |
Confidence-based federated distillation for vision-based lane-centering Y Chen, D Chen, H Wang, K Han, M Zhao 2023 IEEE International Conference on Acoustics, Speech, and Signal …, 2023 | 4 | 2023 |
EPAM: A predictive energy model for mobile AI A Mallik, H Wang, J Xie, D Chen, K Han ICC 2023-IEEE International Conference on Communications, 954-959, 2023 | 4 | 2023 |
Poster: Enabling high-fidelity and real-time mobility digital twin with edge computing Y Liu, H Wang, Z Cai, D Chen, K Han 2022 IEEE/ACM 7th Symposium on Edge Computing (SEC), 281-283, 2022 | 4 | 2022 |
Love of variety based latency analysis for high definition map updating: Age of information and distributional robust perspectives D Chen, Y Zhu, D Wang, H Wang, J Xie, XP Zhang, Z Han IEEE Transactions on Intelligent Vehicles 8 (2), 1751-1764, 2022 | 4 | 2022 |
Incentive mechanisms for federated learning CS Hong, LU Khan, M Chen, D Chen, W Saad, Z Han, C Seon Hong, ... Federated Learning for Wireless Networks, 71-128, 2021 | 4 | 2021 |
CoMap: Proactive Provision for Crowdsourcing Map in Automotive Edge Computing Y Xue, Y Zhang, Q Liu, D Chen, K Han ICC 2023-IEEE International Conference on Communications, 3252-3257, 2023 | 3 | 2023 |