Minghong Fang
Minghong Fang
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα iastate.edu
Παρατίθεται από
Παρατίθεται από
Local model poisoning attacks to Byzantine-robust federated learning
M Fang, X Cao, J Jia, N Gong
29th {USENIX} Security Symposium ({USENIX} Security 20), 1605-1622, 2020
Poisoning attacks to graph-based recommender systems
M Fang, G Yang, NZ Gong, J Liu
Proceedings of the 34th Annual Computer Security Applications Conference …, 2018
Influence function based data poisoning attacks to top-n recommender systems
M Fang, NZ Gong, J Liu
Proceedings of The Web Conference 2020, 3019-3025, 2020
Byzantine-resilient stochastic gradient descent for distributed learning: A lipschitz-inspired coordinate-wise median approach
H Yang, X Zhang, M Fang, J Liu
2019 IEEE 58th Conference on Decision and Control (CDC), 5832-5837, 2019
Prioritizing disease-causing genes based on network diffusion and rank concordance
M Fang, X Hu, T He, Y Wang, J Zhao, X Shen, J Yuan
2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2014
Private and communication-efficient edge learning: a sparse differential gaussian-masking distributed SGD approach
X Zhang, M Fang, J Liu, Z Zhu
Proceedings of the Twenty-First International Symposium on Theory …, 2020
A novel disease gene prediction method based on PPI network
J Zhao, T He, X Hu, Y Wang, X Shen, M Fang, J Yuan
2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2014
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping
X Cao, M Fang, J Liu, NZ Gong
arXiv preprint arXiv:2012.13995, 2020
Toward low-cost and stable blockchain networks
M Fang, J Liu
ICC 2020-2020 IEEE International Conference on Communications (ICC), 1-6, 2020
Data Poisoning Attacks and Defenses to Crowdsourcing Systems
M Fang, M Sun, Q Li, NZ Gong, J Tian, J Liu
arXiv preprint arXiv:2102.09171, 2021
Adaptive multi-hierarchical signSGD for communication-efficient distributed optimization
H Yang, X Zhang, M Fang, J Liu
2020 IEEE 21st International Workshop on Signal Processing Advances in …, 2020
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