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  2. Matrix norm - Wikipedia

    en.wikipedia.org/wiki/Matrix_norm

    The Schatten p-norms arise when applying the p-norm to the vector of singular values of a matrix. [2] If the singular values of the m × n {\displaystyle m\times n} matrix A {\displaystyle A} are denoted by σ i , then the Schatten p -norm is defined by

  3. Matrix regularization - Wikipedia

    en.wikipedia.org/wiki/Matrix_regularization

    One example is the squared Frobenius norm, which can be viewed as an -norm acting either entrywise, or on the singular values of the matrix: = ‖ ‖ = | | = ⁡ =. In the multivariate case the effect of regularizing with the Frobenius norm is the same as the vector case; very complex models will have larger norms, and, thus, will be penalized ...

  4. Singular value - Wikipedia

    en.wikipedia.org/wiki/Singular_value

    For example, the Ky Fan-k-norm is the sum of first k singular values, the trace norm is the sum of all singular values, and the Schatten norm is the pth root of the sum of the pth powers of the singular values. Note that each norm is defined only on a special class of operators, hence singular values can be useful in classifying different ...

  5. Schatten norm - Wikipedia

    en.wikipedia.org/wiki/Schatten_norm

    The Schatten 1-norm is the nuclear norm (also known as the trace norm, or the Ky Fan n-norm [1]). The Schatten 2-norm is the Frobenius norm. The Schatten ∞-norm is the spectral norm (also known as the operator norm, or the largest singular value).

  6. Frobenius normal form - Wikipedia

    en.wikipedia.org/wiki/Frobenius_normal_form

    The Frobenius normal form does not reflect any form of factorization of the characteristic polynomial, even if it does exist over the ground field F. This implies that it is invariant when F is replaced by a different field (as long as it contains the entries of the original matrix A ).

  7. Singular value decomposition - Wikipedia

    en.wikipedia.org/wiki/Singular_value_decomposition

    After the algorithm has converged, the singular value decomposition = is recovered as follows: the matrix is the accumulation of Jacobi rotation matrices, the matrix is given by normalising the columns of the transformed matrix , and the singular values are given as the norms of the columns of the transformed matrix .

  8. Specht's theorem - Wikipedia

    en.wikipedia.org/wiki/Specht's_theorem

    If A and B are unitarily equivalent, then tr AA* = tr BB*, where tr denotes the trace (in other words, the Frobenius norm is a unitary invariant). This follows from the cyclic invariance of the trace: if B = U *AU, then tr BB* = tr U *AUU *A*U = tr AUU *A*UU * = tr AA*, where the second equality is cyclic invariance. [3]

  9. Frobenius inner product - Wikipedia

    en.wikipedia.org/wiki/Frobenius_inner_product

    In mathematics, the Frobenius inner product is a binary operation that takes two matrices and returns a scalar.It is often denoted , .The operation is a component-wise inner product of two matrices as though they are vectors, and satisfies the axioms for an inner product.