高维稀疏精度矩阵的有效分布式估计

Efficient Distributed Estimation of High-Dimensional Sparse Precision Matrix

基于去偏的D-trace损失Lasso惩罚方法和阈值方法给出了数据分布在不同机器上高维稀疏精度矩阵的分布式估计.该方法不仅可以实现稀疏精度矩阵的非零元素正确选择,而且误差速率同非分布式估计相当.数值结果进一步表明该方法的有效性.

In this paper, distributed estimation of high-dimensional sparse precision matrix is proposed based on the debiased D-trace loss Lasso penalty method and the threshold method when samples are distributed into different machines. This method achieves the correct selection of non-zero elements of sparse precision matrix, and the error rates can be comparable with estimation in a non-distributed setting. The numerical results further demonstrate that the method is effective.