Logistic regression over encrypted data from fully homomorphic encryption
Abstract Background One of the tasks in the 2017 iDASH secure genome analysis competition was to enable training of logistic regression models over encrypted genomic data. More precisely, given a list of approximately 1500 patient records, each with 18 binary features containing information on speci...
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Main Authors: | Hao Chen (Author), Ran Gilad-Bachrach (Author), Kyoohyung Han (Author), Zhicong Huang (Author), Amir Jalali (Author), Kim Laine (Author), Kristin Lauter (Author) |
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Format: | Book |
Published: |
BMC,
2018-10-01T00:00:00Z.
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Online Access: | Connect to this object online. |
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