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Federated Split Learning With Data and Label Privacy Preservation in Vehicular Networks.

, , , , , , и . IEEE Trans. Veh. Technol., 73 (1): 1223-1238 (января 2024)

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Jinglan Wu

Recovery of citric acid from fermentation broth using simulated moving bed technology: = Reinigung von Zitronensäure aus Fermentationslösung durch kontinuierliche Chromatographie. Uni Erlangen-Nürnberg, (2009)

Jinjin Wu

Haiyan Wu

Yinghua Wu

Changzhu Wu

 

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Collaborative data collection with hybrid vehicular crowd sensing in smart cities., , , и . WCSP, стр. 1-6. IEEE, (2017)A Hierarchical Pseudonyms Management Approach for Software-Defined Vehicular Networks., , , , , и . VTC Spring, стр. 1-5. IEEE, (2016)Scalable Fog Computing with Service Offloading in Bus Networks., , , и . CSCloud, стр. 247-251. IEEE Computer Society, (2016)Evaluation of Inference Attack Models for Deep Learning on Medical Data., , , , , , и . CoRR, (2020)Joint Optimization of Model Partition and Resource Allocation for Split Federated Learning Over Vehicular Edge Networks., , , , , и . IEEE Trans. Veh. Technol., 73 (10): 15860-15865 (октября 2024)Collaborative vehicle sensing in bus networks: A Stackelberg game approach., , , и . ICCC, стр. 1-6. IEEE, (2016)Resting Your Car for Cash: Incentive Mechanism Based TNC Car Scheduling for Carbon Neutrality., , , , , и . ITSC, стр. 1429-1434. IEEE, (2023)Optimized Workload Allocation in Vehicular Edge Computing: A Sequential Game Approach., , , и . ChinaCom (2), том 237 из Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, стр. 542-551. Springer, (2017)To Talk or to Work: Dynamic Batch Sizes Assisted Time Efficient Federated Learning Over Future Mobile Edge Devices., , , , , , и . IEEE Trans. Wirel. Commun., 21 (12): 11038-11050 (2022)Adaptive Privacy Preserving Deep Learning Algorithms for Medical Data., , , , , и . WACV, стр. 1168-1177. IEEE, (2021)