Cloud-based quadratic optimization with partially homomorphic encryption
This paper develops a cloud-based protocol for a constrained quadratic optimization problem involving multiple parties, each holding private data. The protocol is based on the projected gradient ascent on the Lagrange dual problem and exploits partially homomorphic encryption and secure communicatio...
| Главные авторы: | , , , , , |
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| Формат: | Journal article |
| Язык: | English |
| Опубликовано: |
IEEE
2020
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