Yi Liu

Orcid: 0000-0002-0811-6150

Affiliations:
  • City University of Hong Kong
  • Monash University, Faculty of Information Technology, Melbourne, Australia
  • Heilongjiang University, School of Data Science and Technology, Harbin, China (former)


According to our database1, Yi Liu authored at least 36 papers between 2019 and 2024.

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Bibliography

2024
Chiron: A Robustness-Aware Incentive Scheme for Edge Learning via Hierarchical Reinforcement Learning.
IEEE Trans. Mob. Comput., August, 2024

Long-Term Adaptive VCG Auction Mechanism for Sustainable Federated Learning With Periodical Client Shifting.
IEEE Trans. Mob. Comput., May, 2024

BadSampler: Harnessing the Power of Catastrophic Forgetting to Poison Byzantine-robust Federated Learning.
CoRR, 2024

SFP: Spurious Feature-Targeted Pruning for Out-of-Distribution Generalization.
Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

Arondight: Red Teaming Large Vision Language Models with Auto-generated Multi-modal Jailbreak Prompts.
Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

<i>BadSampler: </i> Harnessing the Power of Catastrophic Forgetting to Poison Byzantine-robust Federated Learning.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

2023
Aggregation Service for Federated Learning: An Efficient, Secure, and More Resilient Realization.
IEEE Trans. Dependable Secur. Comput., 2023

SFP: Spurious Feature-targeted Pruning for Out-of-Distribution Generalization.
CoRR, 2023

Cross-Domain Disentangled Learning for E-Commerce Live Streaming Recommendation.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

2022
Towards Communication-Efficient and Attack-Resistant Federated Edge Learning for Industrial Internet of Things.
ACM Trans. Internet Techn., 2022

Resource-Constrained Federated Edge Learning With Heterogeneous Data: Formulation and Analysis.
IEEE Trans. Netw. Sci. Eng., 2022

Communication-Efficient and Cross-Chain Empowered Federated Learning for Artificial Intelligence of Things.
IEEE Trans. Netw. Sci. Eng., 2022

Cross-Area Travel Time Uncertainty Estimation From Trajectory Data: A Federated Learning Approach.
IEEE Trans. Intell. Transp. Syst., 2022

Semi-Supervised Federated Learning for Travel Mode Identification From GPS Trajectories.
IEEE Trans. Intell. Transp. Syst., 2022

Efficient Stein Variational Inference for Reliable Distribution-lossless Network Pruning.
CoRR, 2022

CaDM: Codec-aware Diffusion Modeling for Neural-enhanced Video Streaming.
CoRR, 2022

Feature Correlation-guided Knowledge Transfer for Federated Self-supervised Learning.
CoRR, 2022

Hierarchical Channel-spatial Encoding for Communication-efficient Collaborative Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

The Right to be Forgotten in Federated Learning: An Efficient Realization with Rapid Retraining.
Proceedings of the IEEE INFOCOM 2022, 2022

Sustainable Federated Learning with Long-term Online VCG Auction Mechanism.
Proceedings of the 42nd IEEE International Conference on Distributed Computing Systems, 2022

MCSCSet: A Specialist-annotated Dataset for Medical-domain Chinese Spelling Correction.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021
Federated Learning in the Sky: Aerial-Ground Air Quality Sensing Framework With UAV Swarms.
IEEE Internet Things J., 2021

Deep Anomaly Detection for Time-Series Data in Industrial IoT: A Communication-Efficient On-Device Federated Learning Approach.
IEEE Internet Things J., 2021

Incentive-Driven Long-term Optimization for Edge Learning by Hierarchical Reinforcement Mechanism.
Proceedings of the 41st IEEE International Conference on Distributed Computing Systems, 2021

2020
A Secure Federated Learning Framework for 5G Networks.
IEEE Wirel. Commun., 2020

Dominant Data Set Selection Algorithms for Electricity Consumption Time-Series Data Analysis Based on Affine Transformation.
IEEE Internet Things J., 2020

Privacy-Preserving Traffic Flow Prediction: A Federated Learning Approach.
IEEE Internet Things J., 2020

RC-SSFL: Towards Robust and Communication-efficient Semi-supervised Federated Learning System.
CoRR, 2020

Federated Learning for 6G Communications: Challenges, Methods, and Future Directions.
CoRR, 2020

FedGRU: Privacy-preserving Traffic Flow Prediction via Federated Learning.
Proceedings of the 23rd IEEE International Conference on Intelligent Transportation Systems, 2020

Robust Federated Learning Approach for Travel Mode Identification from Non-IID GPS Trajectories.
Proceedings of the 26th IEEE International Conference on Parallel and Distributed Systems, 2020

Communication-Efficient Federated Learning for Anomaly Detection in Industrial Internet of Things.
Proceedings of the IEEE Global Communications Conference, 2020

Scalable and Communication-Efficient Decentralized Federated Edge Learning with Multi-blockchain Framework.
Proceedings of the Blockchain and Trustworthy Systems - Second International Conference, 2020

2019
Big Data Platform Architecture Under The Background of Financial Technology.
CoRR, 2019

Spatial-Temporal Graph Attention Networks: A Deep Learning Approach for Traffic Forecasting.
IEEE Access, 2019

PPGAN: Privacy-Preserving Generative Adversarial Network.
Proceedings of the 25th IEEE International Conference on Parallel and Distributed Systems, 2019


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