论文标题
先验用马蹄形进行压缩传感的相变
Phase transition in compressed sensing with horseshoe prior
论文作者
论文摘要
在贝叶斯统计数据中，马蹄批准吸引了越来越多的关注，作为稀疏估计的一种方法。通过统计机械方法评估压缩感测的估计精度。发现在观测值数量和非零信号数量的平面中，信号可恢复性的相变存在，并且比使用众所周知的$ L_1 $ norm norm正规化的恢复性阶段更扩展。
In Bayesian statistics, horseshoe prior has attracted increasing attention as an approach to the sparse estimation. The estimation accuracy of compressed sensing with the horseshoe prior is evaluated by statistical mechanical method. It is found that there exists a phase transition in signal recoverability in the plane of the number of observations and the number of nonzero signals and that the recoverability phase is more extended than that using the well-known $l_1$ norm regularization.
