Hu, Rui, Guo, Yuanxiong, and Gong, Yanmin. Federated Learning With Sparsified Model Perturbation: Improving Accuracy Under Client-Level Differential Privacy. Retrieved from https://par.nsf.gov/biblio/10530030. IEEE Transactions on Mobile Computing 23.8 Web. doi:10.1109/TMC.2023.3343288.

Hu, Rui, Guo, Yuanxiong, & Gong, Yanmin. Federated Learning With Sparsified Model Perturbation: Improving Accuracy Under Client-Level Differential Privacy. IEEE Transactions on Mobile Computing, 23 (8). Retrieved from https://par.nsf.gov/biblio/10530030. https://doi.org/10.1109/TMC.2023.3343288

Hu, Rui, Guo, Yuanxiong, and Gong, Yanmin. "Federated Learning With Sparsified Model Perturbation: Improving Accuracy Under Client-Level Differential Privacy". IEEE Transactions on Mobile Computing 23 (8). Country unknown/Code not available: IEEE. https://doi.org/10.1109/TMC.2023.3343288. https://par.nsf.gov/biblio/10530030.

@article{osti_10530030,
place = {Country unknown/Code not available}, title = {Federated Learning With Sparsified Model Perturbation: Improving Accuracy Under Client-Level Differential Privacy}, url = {https://par.nsf.gov/biblio/10530030}, DOI = {10.1109/TMC.2023.3343288}, abstractNote = {}, journal = {IEEE Transactions on Mobile Computing}, volume = {23}, number = {8}, publisher = {IEEE}, author = {Hu, Rui and Guo, Yuanxiong and Gong, Yanmin}, }