Wenjie Li

Orcid: 0000-0003-2717-9031

Affiliations:
  • Tsinghua University, Beijing, China


According to our database1, Wenjie Li authored at least 14 papers between 2020 and 2024.

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

Timeline

Legend:

Book 
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Article 
PhD thesis 
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Links

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Bibliography

2024
A Game-theoretic Framework for Privacy-preserving Federated Learning.
ACM Trans. Intell. Syst. Technol., June, 2024

Node-Level Graph Regression With Deep Gaussian Process Models.
IEEE Trans. Artif. Intell., June, 2024

PBFL: Privacy-Preserving and Byzantine-Robust Federated-Learning-Empowered Industry 4.0.
IEEE Internet Things J., February, 2024

FLSG: A Novel Defense Strategy Against Inference Attacks in Vertical Federated Learning.
IEEE Internet Things J., January, 2024

Enhancing Security and Privacy in Federated Learning using Update Digests and Voting-Based Defense.
CoRR, 2024

ReFer: Retrieval-Enhanced Vertical Federated Recommendation for Full Set User Benefit.
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

2023
Theoretically Principled Federated Learning for Balancing Privacy and Utility.
CoRR, 2023

A Game-theoretic Framework for Federated Learning.
CoRR, 2023

2022
Vertical Semi-Federated Learning for Efficient Online Advertising.
CoRR, 2022

Semi-Supervised Cross-Silo Advertising with Partial Knowledge Transfer.
CoRR, 2022

Deep Dirichlet process mixture models.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

2021
H-GPR: A Hybrid Strategy for Large-Scale Gaussian Process Regression.
Proceedings of the IEEE International Conference on Acoustics, 2021

2020
Stochastic Deep Gaussian Processes over Graphs.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

SDCN: Sparsity and Diversity Driven Correlation Networks for Traffic Demand Forecasting.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020


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