Liang, Zhicong, Wang, Bao, Gu, Quanquan, Osher, Stanley, and Yao, Yuan. Differentially private federated learning with Laplacian smoothing. Retrieved from https://par.nsf.gov/biblio/10514435. Applied and Computational Harmonic Analysis 72.C Web. doi:10.1016/j.acha.2024.101660.

Liang, Zhicong, Wang, Bao, Gu, Quanquan, Osher, Stanley, & Yao, Yuan. Differentially private federated learning with Laplacian smoothing. Applied and Computational Harmonic Analysis, 72 (C). Retrieved from https://par.nsf.gov/biblio/10514435. https://doi.org/10.1016/j.acha.2024.101660

Liang, Zhicong, Wang, Bao, Gu, Quanquan, Osher, Stanley, and Yao, Yuan. "Differentially private federated learning with Laplacian smoothing". Applied and Computational Harmonic Analysis 72 (C). Country unknown/Code not available: ScienceDirect. https://doi.org/10.1016/j.acha.2024.101660. https://par.nsf.gov/biblio/10514435.

@article{osti_10514435,
place = {Country unknown/Code not available}, title = {Differentially private federated learning with Laplacian smoothing}, url = {https://par.nsf.gov/biblio/10514435}, DOI = {10.1016/j.acha.2024.101660}, abstractNote = {}, journal = {Applied and Computational Harmonic Analysis}, volume = {72}, number = {C}, publisher = {ScienceDirect}, author = {Liang, Zhicong and Wang, Bao and Gu, Quanquan and Osher, Stanley and Yao, Yuan}, }