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Wei Ni — most-cited papers & profile · AI Agents
← authors
·
overview
Wei Ni
34
papers ·
31
citations ·
39
h-index
Edith Cowan University · Commonwealth Scientific and Industrial Research Organisation · Fudan University · UNSW Sydney · Mianyang City Center for Disease Control and Prevention
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Most-cited papers
IronForge: An Open, Secure, Fair, Decentralized Federated Learning
2023 · 4 citations
A Secure Aggregation for Federated Learning on Long-Tailed Data
2023 · 3 citations
Data-Agnostic Model Poisoning against Federated Learning: A Graph Autoencoder Approach
2023 · 3 citations
On-board Deep Q-Network for UAV-assisted Online Power Transfer and Data Collection
2019 · 2 citations
Exploring Deep Reinforcement Learning-Assisted Federated Learning for Online Resource Allocation in Privacy-Persevering EdgeIoT
2022 · 2 citations
Exploring Deep Reinforcement Learning-Assisted Federated Learning for Online Resource Allocation in Privacy-Persevering EdgeIoT
2022 · 2 citations
Amplitude-Varying Perturbation for Balancing Privacy and Utility in Federated Learning
2023 · 2 citations
Blockchained Federated Learning for Internet of Things: A Comprehensive Survey
2023 · 2 citations
Over-The-Air Federated Learning: Status Quo, Open Challenges, and Future Directions
2023 · 2 citations
Data and Model Poisoning Backdoor Attacks on Wireless Federated Learning, and the Defense Mechanisms: A Comprehensive Survey
2023 · 2 citations
Data and Model Poisoning Backdoor Attacks on Wireless Federated Learning, and the Defense Mechanisms: A Comprehensive Survey
2023 · 2 citations
BlockFUL: Enabling Unlearning in Blockchained Federated Learning
2024 · 1 citations
Dataset Obfuscation: Its Applications to and Impacts on Edge Machine Learning
2022 · 1 citations
New Adversarial Image Detection Based on Sentiment Analysis
2023 · 1 citations
Towards Dynamic Resource Allocation and Client Scheduling in Hierarchical Federated Learning: A Two-Phase Deep Reinforcement Learning Approach
2024 · 1 citations
Topics
Federated Learning
Communication
Privacy
Edge Computing
Adversarial ML
Data Heterogeneity
Policy Gradient
Model-Based RL
Anomaly Detection
Vulnerability Detection