Given a Matrix $A$ we can use Simultaneous iteration(Using power iteration on all columns simultaneously) to compute the d biggest eigenvalues. Now this method will give you the biggest eigenvalues, but how can u find the smallest eigenvalues? Maybe by using it on the $A^{-1} $, or am i completely wrong?
Edit: So basically if you use simultaneous iteration on $A^{-1} $ you will find the biggest eigenvalues which then are the smallest eigenvalues of $A$