Hard-thresholding-based algorithms have seen various advantages for sparse optimization in controlling the sparsity and allowing fast computation. Recent research shows that when techniques of Newton-type methods are integrated, their numerical performance can be improved surprisingly. This paper develops a gradient projection Newton pursuit algorithm mainly adopts hard-thresholding operator em...

In order to summarize and represent graphically multidimensional data in statistics, projection pursuit methods look for projection axes which reveal structures, such as possible groups or outliers, by optimizing a function called projection index. To determine these possible interesting structures, it is necessary to choose an optimization method capable to find not only the global optimum of ...