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您的检索式：作者名="Shigong Long"
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| 1 | A federated learning scheme meets dynamic differential privacy显示文摘Federated learning is a widely used distributed learning approach in recent years,however,despite model training from collecting data become to gathering parameters,privacy violations may occur when publishing and sharing models.A dynamic approach is pro-posed to add Gaussian noise more effectively and apply differential privacy to federal deep learning.Concretely,it is abandoning the traditional way of equally distributing the privacy budget e and adjusting the privacy budget to accommodate gradient descent federation learning dynamically,where the parameters depend on computation derived to avoid the impact on the algorithm that hyperparameters are created manually.It also incorporates adaptive threshold cropping to control the sensitivity,and finally,moments accountant is used to counting the∈consumed on the privacy‐preserving,and learning is stopped only if the∈_(total)by clients setting is reached,this allows the privacy budget to be adequately explored for model training.The experimental results on real datasets show that the method training has almost the same effect as the model learning of non‐privacy,which is significantly better than the differential privacy method used by TensorFlow. | Shengnan Guo Xibin Wang Shigong Long Hai Liu Liu Hai Toong Hai Sam | 2023 | CAAI Transactions on Intelligence Technology2023，8，3： | 0 |
| 2 | Federated learning privacy incentives:Reverse auctions and negotiations显示文摘The incentive mechanism of federated learning has been a hot topic,but little research has been done on the compensation of privacy loss.To this end,this study uses the Local SGD federal learning framework and gives a theoretical analysis under the use of differential privacy protection.Based on the analysis,a multi‐attribute reverse auction model is proposed to be used for user selection as well as payment calculation for participation in federal learning.The model uses a mixture of economic and non‐economic attributes in making choices for users and is transformed into an optimisation equation to solve the user choice problem.In addition,a post‐auction negotiation model that uses the Rubinstein bargaining model as well as optimisation equations to describe the negotiation process and theoretically demonstrate the improvement of social welfare is proposed.In the experimental part,the authors find that their algorithm improves both the model accuracy and the F1‐score values relative to the comparison algorithms to varying degrees. | Hongqin Lyu Yongxiong Zhang Chao Wang Shigong Long Shengnan Guo | 2023 | CAAI Transactions on Intelligence Technology2023，8，4： | 0 |
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