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For two matrices (or two trees), the alternative hypothesis (H1) is that the inferred trees are partially or completely congruent.
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Specifically, the BO formulation may fail due to crossing of the eigenvalues of the covariance matrix, while both BO and DO become unstable when there is a high condition number of the covariance matrix or zero eigenvalues.
Each matrix-matrix multiplication requires three matrices (two input matrices and one result matrix) in memory during execution.
A caveat of this correlation model is that the size of a cluster may be driven by one to two assays in the chemical similarity matrix or one or two chemicals in the assay similarity matrix.
This actuator combines four shape memory alloy (SMA) wires embedded in a soft matrix where one or two SMA wires can be activated to induce the actuator into either the bending mode, the twisting mode or the combined bending and twisting mode of actuation.
Nevertheless, we can rule out the possibility that in our task they learned two independent matrices of pairwise choices or two independent rank orders because when they were first presented with choices between one numeral and one dot array (Fig. 3e), they immediately started to choose, accurately, the larger one, irrespective of modality.
When damages take place in matrix or in fiber matrix interface without fibers involved in, the material shows lower strength, and the stress strain curves present linear and brittle behavior.
When more than two matrices (or trees) are tested, H1 postulates that at least two trees in the group are partially or completely congruent.
Matrix A that defines admissible set in problem (8) has a simple structure: each row of matrix A contains one or two non-zero elements.
Wipf and Nagarajan (2008) proposed an algorithm that finds the solution of the sparse regression problem using automatic relevance determination (ARD) (7) where the hyper-parameter matrix Γ is a diagonal matrix with positive or zero entries along the diagonal.
For these methods, there is an assumption that the length of vector from two matrices or matrix itself should be same in order to calculate the similarity.
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