most citedA stochastic gradient descent approach with partitioned-truncated singular value decomposition for large-scale inverse problems of magnetic modulus data

5 citations · 5 across the 1 of their papers we have counts for

collaborators

1 paper

math.NA2022★ 5 cited

A stochastic gradient descent approach with partitioned-truncated singular value decomposition for large-scale inverse problems of magnetic modulus data

Wenbin Li, Kangzhi Wang, Tingting Fan

We propose a stochastic gradient descent approach with partitioned-truncated singular value decomposition for large-scale inverse problems of magnetic modulus data. Motivated by a…