Zijia Mo

Orcid: 0000-0001-5853-2155

According to our database1, Zijia Mo authored at least 23 papers between 2019 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
IDDANet: An Input-Driven Dynamic Adaptive Network ensemble method for edge intelligence.
Future Gener. Comput. Syst., November, 2023

FedUSC: Collaborative Unsupervised Representation Learning From Decentralized Data for Internet of Things.
IEEE Internet Things J., August, 2023

FedSup: A communication-efficient federated learning fatigue driving behaviors supervision approach.
Future Gener. Comput. Syst., 2023

Precision-Mixed and Weight-Average Ensemble: Online Knowledge Distillation for Quantization Convolutional Neural Networks.
Proceedings of the IEEE Wireless Communications and Networking Conference, 2023

Data-Efficient Adaptive Global Pruning for Convolutional Neural Networks in Edge Computing.
Proceedings of the IEEE International Conference on Communications, 2023

FedSC: Compatible Gradient Compression for Communication-Efficient Federated Learning.
Proceedings of the Algorithms and Architectures for Parallel Processing, 2023

2022
FedDQ: A communication-efficient federated learning approach for Internet of Vehicles.
J. Syst. Archit., 2022

AFL: An Adaptively Federated Multitask Learning for Model Sharing in Industrial IoT.
IEEE Internet Things J., 2022

FedGAN: A Federated Semi-supervised Learning from Non-IID Data.
Proceedings of the Wireless Algorithms, Systems, and Applications, 2022

CFedPer: Clustered Federated Learning with Two-Stages Optimization for Personalization.
Proceedings of the 18th International Conference on Mobility, Sensing and Networking, 2022

FedACL: Federated Multi-Distillation with Auxiliary Classification Layers in IoT.
Proceedings of the 24th IEEE Int Conf on High Performance Computing & Communications; 8th Int Conf on Data Science & Systems; 20th Int Conf on Smart City; 8th Int Conf on Dependability in Sensor, 2022

FedCL: An Efficient Federated Unsupervised Learning for Model Sharing in IoT.
Proceedings of the Collaborative Computing: Networking, Applications and Worksharing, 2022

2021
FedSup: A Communication-Efficient Federated Learning Fatigue Driving Behaviors Supervision Framework.
CoRR, 2021

Triple-partition Network: Collaborative Neural Network based on the 'End Device-Edge-Cloud'.
Proceedings of the IEEE Wireless Communications and Networking Conference, 2021

Select-Storage: A New Oracle Design Pattern on Blockchain.
Proceedings of the 20th IEEE International Conference on Trust, 2021

FedIM: An Anti-attack Federated Learning Based on Agent Importance Aggregation.
Proceedings of the 20th IEEE International Conference on Trust, 2021

A Model Training Mechanism based on Onchain and Offchain Collaboration for Edge Computing.
Proceedings of the ICC 2021, 2021

EdgeSP: Scalable Multi-device Parallel DNN Inference on Heterogeneous Edge Clusters.
Proceedings of the Algorithms and Architectures for Parallel Processing, 2021

2019
Task Offloading and Resources Allocation based on Fairness in Edge Computing.
Proceedings of the 2019 IEEE Wireless Communications and Networking Conference, 2019

Deep Reinforcement Learning Based Service Migration Strategy for Edge Computing.
Proceedings of the 13th IEEE International Conference on Service-Oriented System Engineering, 2019

A Credible and Lightweight Multidimensional Trust Evaluation Mechanism for Service-Oriented IoT Edge Computing Environment.
Proceedings of the 2019 IEEE International Congress on Internet of Things, 2019

A Data Uploading Strategy in Vehicular Ad-hoc Networks Targeted on Dynamic Topology: Clustering and Cooperation.
Proceedings of the Algorithms and Architectures for Parallel Processing, 2019

A Real-Time Task Offloading Strategy Based on Double Auction for Optimal Resource Allocation in Edge Computing.
Proceedings of the 7th International Conference on Future Internet of Things and Cloud, 2019


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