Hanlin Gu

Orcid: 0000-0001-8266-4561

According to our database1, Hanlin Gu authored at least 32 papers between 2018 and 2025.

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

Timeline

2018
2019
2020
2021
2022
2023
2024
2025
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5
10
15
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10
9
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5
3
1

Legend:

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In proceedings 
Article 
PhD thesis 
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Other 

Links

On csauthors.net:

Bibliography

2025
FedTracker: Furnishing Ownership Verification and Traceability for Federated Learning Model.
IEEE Trans. Dependable Secur. Comput., 2025

FedMKT: Federated Mutual Knowledge Transfer for Large and Small Language Models.
Proceedings of the 31st International Conference on Computational Linguistics, 2025

2024
Optimizing Privacy, Utility, and Efficiency in a Constrained Multi-Objective Federated Learning Framework.
ACM Trans. Intell. Syst. Technol., December, 2024

FedCut: A Spectral Analysis Framework for Reliable Detection of Byzantine Colluders.
IEEE Trans. Pattern Anal. Mach. Intell., September, 2024

A Communication Theory Perspective on Prompting Engineering Methods for Large Language Models.
J. Comput. Sci. Technol., July, 2024

Addressing Spatial-Temporal Data Heterogeneity in Federated Continual Learning via Tail Anchor.
CoRR, 2024

Disentangling data distribution for Federated Learning.
CoRR, 2024

A few-shot Label Unlearning in Vertical Federated Learning.
CoRR, 2024

PDSS: A Privacy-Preserving Framework for Step-by-Step Distillation of Large Language Models.
CoRR, 2024

FedAdOb: Privacy-Preserving Federated Deep Learning with Adaptive Obfuscation.
CoRR, 2024

Federated Domain-Specific Knowledge Transfer on Large Language Models Using Synthetic Data.
CoRR, 2024

Evaluating Membership Inference Attacks and Defenses in Federated Learning.
CoRR, 2024

Label Privacy Source Coding in Vertical Federated Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

Ferrari: Federated Feature Unlearning via Optimizing Feature Sensitivity.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Unlearning during Learning: An Efficient Federated Machine Unlearning Method.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Byzantine Robust Aggregation in Federated Distillation with Adversaries.
Proceedings of the 44th IEEE International Conference on Distributed Computing Systems, 2024

Diffusion-Driven Data Replay: A Novel Approach to Combat Forgetting in Federated Class Continual Learning.
Proceedings of the Computer Vision - ECCV 2024, 2024

2023
FedIPR: Ownership Verification for Federated Deep Neural Network Models.
IEEE Trans. Pattern Anal. Mach. Intell., April, 2023

No Free Lunch Theorem for Security and Utility in Federated Learning.
ACM Trans. Intell. Syst. Technol., February, 2023

A Theoretical Analysis of Efficiency Constrained Utility-Privacy Bi-Objective Optimization in Federated Learning.
CoRR, 2023

Grounding Foundation Models through Federated Transfer Learning: A General Framework.
CoRR, 2023

A Communication Theory Perspective on Prompting Engineering Methods for Large Language Models.
CoRR, 2023

Temporal Gradient Inversion Attacks with Robust Optimization.
CoRR, 2023

FedSOV: Federated Model Secure Ownership Verification with Unforgeable Signature.
CoRR, 2023

FedZKP: Federated Model Ownership Verification with Zero-knowledge Proof.
CoRR, 2023

Optimizing Privacy, Utility and Efficiency in Constrained Multi-Objective Federated Learning.
CoRR, 2023

Achieving Provable Byzantine Fault-tolerance in a Semi-honest Federated Learning Setting.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2023

FedPDD: A Privacy-preserving Double Distillation Framework for Cross-silo Federated Recommendation.
Proceedings of the International Joint Conference on Neural Networks, 2023

FedPass: Privacy-Preserving Vertical Federated Deep Learning with Adaptive Obfuscation.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

2022
FedTracker: Furnishing Ownership Verification and Traceability for Federated Learning Model.
CoRR, 2022

2021
Federated Deep Learning with Bayesian Privacy.
CoRR, 2021

2018
Data-Driven Tight Frame for CRYO-EM Image Denoising and Conformational Classification.
Proceedings of the 2018 IEEE Global Conference on Signal and Information Processing, 2018


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