论文标题
通过统计物理学的高维线性回归的确切结果
Exact results on high-dimensional linear regression via statistical physics
论文作者
论文摘要
显然，需要修改常规的统计推理协议，以正确处理现在常见的高维数据。旨在实现此修订的最新研究取决于强大的近似技术，这些技术呼吁对其进行严格的结果进行测试。在这种情况下，高维线性回归的最简单情况已获得了重要的新相关性和关注。在本文中，我们使用有关推断的统计物理学观点来得出高维状态中线性回归的许多新的确切结果。
It is clear that conventional statistical inference protocols need to be revised to deal correctly with the high-dimensional data that are now common. Most recent studies aimed at achieving this revision rely on powerful approximation techniques, that call for rigorous results against which they can be tested. In this context, the simplest case of high-dimensional linear regression has acquired significant new relevance and attention. In this paper we use the statistical physics perspective on inference to derive a number of new exact results for linear regression in the high-dimensional regime.
