Sheng Shen

Orcid: 0000-0003-4734-1008

Affiliations:
  • University of Sydney, School of Electrical and Information Engineering, NSW, Australia


According to our database1, Sheng Shen authored at least 19 papers between 2019 and 2025.

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

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2025
Reinforcement Unlearning.
Proceedings of the 32nd Annual Network and Distributed System Security Symposium, 2025

2024
Federated Learning With Heterogeneous Client Expectations: A Game Theory Approach.
IEEE Trans. Knowl. Data Eng., December, 2024

Privacy preservation in deep reinforcement learning: A training perspective.
Knowl. Based Syst., 2024

A GNN-based teacher-student framework with multi-advice.
Expert Syst. Appl., 2024

Federated Multi-Agent Reinforcement Learning for Heterogeneous Action Spaces.
Proceedings of the 99th IEEE Vehicular Technology Conference, 2024

2023
Multi-Agent Reinforcement Learning for Online Food Delivery with Location Privacy Preservation.
Inf., 2023

Reinforcement Unlearning.
CoRR, 2023

New challenges in reinforcement learning: a survey of security and privacy.
Artif. Intell. Rev., 2023

Wireless Decentralized Federated Learning with Energy-Constrained Clients.
Proceedings of the 9th IEEE World Forum on Internet of Things, 2023

Towards Robust Gan-Generated Image Detection: A Multi-View Completion Representation.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

2022
One Parameter Defense - Defending Against Data Inference Attacks via Differential Privacy.
IEEE Trans. Inf. Forensics Secur., 2022

Differentially Private Multi-Agent Planning for Logistic-Like Problems.
IEEE Trans. Dependable Secur. Comput., 2022

A novel differentially private advising framework in cloud server environment.
Concurr. Comput. Pract. Exp., 2022

From distributed machine learning to federated learning: In the view of data privacy and security.
Concurr. Comput. Pract. Exp., 2022

2021
A Differentially Private Game Theoretic Approach for Deceiving Cyber Adversaries.
IEEE Trans. Inf. Forensics Secur., 2021

An optimized differential privacy scheme with reinforcement learning in VANET.
Comput. Secur., 2021

2020
Model Poisoning Defense on Federated Learning: A Validation Based Approach.
Proceedings of the Network and System Security - 14th International Conference, 2020

2019
Differential Privacy Preservation for Smart Meter Systems.
Proceedings of the Algorithms and Architectures for Parallel Processing, 2019

Simultaneously Advising via Differential Privacy in Cloud Servers Environment.
Proceedings of the Algorithms and Architectures for Parallel Processing, 2019


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