We discuss an alternating least squares algorithm that uses both decomposition and block relaxation to find the optimal positive semidefinite approxation of given rank p to a known symmetric matrix of order n. Each iteration of the algorithm involves minimizing n quartics and solving n secular equations of order p.
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