  We present a simple formula to update the pseudoinverse of a full-rank
rectangular matrix that undergoes a low-rank modification, and demonstrate its
utility for solving least squares problems. The resulting algorithm can be
dramatically faster than solving the modified least squares problem from
scratch, just like the speedup enabled by Sherman--Morrison--Woodbury for
solving linear systems with low-rank modifications.
