Abstract:The NP-hard maximum-entropy sampling problem (MESP) seeks a maximum (log-)determinant principal submatrix, of a given order, from an input covariance matrix C.We give an efficient dynamic-programming algorithm for MESP when C (or its inverse) is tridiagonal and generalize it to the situation where the support graph of C (or its inverse) is a spider graph (and beyond). We give a class of arrowhead covariance matrices C for which a natural greedy algorithm solves MESP.A mask M for MESP is a correlation matrix wi… Show more
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