… Gram matrix are presented. Based on these properties new techniques for the computation
of Gram matrix … terms: Gram matrix, reciprocal system, impulse-response Gramian, Markov …

… activity patterns by Gram matrices and identifying anomalies in Gram matrix values can yield
high OOD detection rates. We identify anomalies in the Gram matrices by simply comparing …

… concentration of sums of eigenvalues of a Gram matrix gained from a finite sample of vectors,
… Gram matrix and those of the underlying process. For a given kernel function and density …

… In addition to developing and analyzing an algorithm which provides a provably good
decomposition of a Gram matrix, which may then be used to speed up kernel-based learning …

… ) system is carried out analyzing the pivots of the Gram matrix. The Gram matrix can also be
used to verify local redundancy, which is … Others features of the Gram matrix are under study. …

… of the Gram matrix WTW built upon a collection w1,...,wn ∈ Rp … are some non negative definite
p×p matrices. The cardinality na of class Ca … In this article, we consider the Gram matrix W …

… Gram matrix for this basis, and is Hermitian positive definite. If we denote by cr(A) the spectrum
(set of eigenvalues) of the matrix A … for the P-condition number of the Gram matrix (1.4) is …

… , we report numerical results for the Gram matrix defined by the weighted Vandermonde-like
matrix for least squares approximation on an interval and for the Gram matrix defined by an …

… Gram matrix is sparse, in which case sparse matrix computation methods may be used, in
other applications the Gram matrix is … that compute such an approximation to a Gram matrix G. …

… matrices of rank d. For a detailed discussion of the relation between positive semidefinite
matrices, Gram matrices, and square-distance matrices, … the space of these matrices, called the …