We detail distributed algorithms for scalable, secure multiparty linear regression and feature selection at essentially the same speed as plaintext regression. While the core geometric ideas are simple, the recognition of their broad utility when combined is novel. Our scheme opens the door to efficient and secure genome-wide association studies across multiple biobanks.
翻译:我们详细描述了可缩放、安全的多党线性回归和特征选择的分布算法,其速度基本上与纯文本回归相同。 虽然核心几何概念很简单,但当结合时对其广泛效用的承认是新奇的。 我们的计划打开了跨多个生物库高效和安全地进行基因组联系研究的大门。