Peng, Hongwu, Zhou, Shanglin, Luo, Yukui, Xu, Nuo, Duan, Shijin, Ran, Ran, Zhao, Jiahui, Wang, Chenghong, Geng, Tong, Wen, Wujie, Xu, Xiaolin, and Ding, Caiwen. PASNet: Polynomial Architecture Search Framework for Two-party Computation-based Secure Neural Network Deployment. Retrieved from https://par.nsf.gov/biblio/10463761. 2023 60th ACM/IEEE Design Automation Conference (DAC) . Web. doi:10.1109/DAC56929.2023.10247663.

Peng, Hongwu, Zhou, Shanglin, Luo, Yukui, Xu, Nuo, Duan, Shijin, Ran, Ran, Zhao, Jiahui, Wang, Chenghong, Geng, Tong, Wen, Wujie, Xu, Xiaolin, & Ding, Caiwen. PASNet: Polynomial Architecture Search Framework for Two-party Computation-based Secure Neural Network Deployment. 2023 60th ACM/IEEE Design Automation Conference (DAC), (). Retrieved from https://par.nsf.gov/biblio/10463761. https://doi.org/10.1109/DAC56929.2023.10247663

Peng, Hongwu, Zhou, Shanglin, Luo, Yukui, Xu, Nuo, Duan, Shijin, Ran, Ran, Zhao, Jiahui, Wang, Chenghong, Geng, Tong, Wen, Wujie, Xu, Xiaolin, and Ding, Caiwen. "PASNet: Polynomial Architecture Search Framework for Two-party Computation-based Secure Neural Network Deployment". 2023 60th ACM/IEEE Design Automation Conference (DAC) (). Country unknown/Code not available. https://doi.org/10.1109/DAC56929.2023.10247663. https://par.nsf.gov/biblio/10463761.

@article{osti_10463761,
place = {Country unknown/Code not available}, title = {PASNet: Polynomial Architecture Search Framework for Two-party Computation-based Secure Neural Network Deployment}, url = {https://par.nsf.gov/biblio/10463761}, DOI = {10.1109/DAC56929.2023.10247663}, abstractNote = {}, journal = {2023 60th ACM/IEEE Design Automation Conference (DAC)}, author = {Peng, Hongwu and Zhou, Shanglin and Luo, Yukui and Xu, Nuo and Duan, Shijin and Ran, Ran and Zhao, Jiahui and Wang, Chenghong and Geng, Tong and Wen, Wujie and Xu, Xiaolin and Ding, Caiwen}, }