CHET: an optimizing compiler for fully-homomorphic neural-network inferencing-Reference-Cited by-同舟云学术

CHET: an optimizing compiler for fully-homomorphic neural-network inferencing

Published:2019-06-08 Issue: Volume: Page:
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Container-title:Proceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation
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Author:

Dathathri Roshan¹,Saarikivi Olli²,Chen Hao²,Laine Kim²,Lauter Kristin²,Maleki Saeed²,Musuvathi Madanlal²,Mytkowicz Todd²

Affiliation:

1. University of Texas at Austin, USA

2. Microsoft Research, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3314221.3314628

Reference42 articles.

1. Abbas Acar Hidayet Aksu A. Selcuk Uluagac and Mauro Conti. 2017. A Survey on Homomorphic Encryption Schemes: Theory and Implementation. CoRR abs/1704.03578 (2017). arXiv:1704.03578 http://arxiv.org/abs/1704.03578. Abbas Acar Hidayet Aksu A. Selcuk Uluagac and Mauro Conti. 2017. A Survey on Homomorphic Encryption Schemes: Theory and Implementation. CoRR abs/1704.03578 (2017). arXiv:1704.03578 http://arxiv.org/abs/1704.03578.

2. Improved Security for a Ring-Based Fully Homomorphic Encryption Scheme. In Cryptography and Coding, Martijn Stam (Ed.). Springer Berlin Heidelberg, Berlin;Bos Joppe W.;Heidelberg,2013

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