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  2. Kernel (linear algebra) - Wikipedia

    en.wikipedia.org/wiki/Kernel_(linear_algebra)

    The kernel of a m × n matrix A over a field K is a linear subspace of K n. That is, the kernel of A, the set Null(A), has the following three properties: Null(A) always contains the zero vector, since A0 = 0. If x ∈ Null(A) and y ∈ Null(A), then x + y ∈ Null(A). This follows from the distributivity of matrix multiplication over addition.

  3. Jacobian matrix and determinant - Wikipedia

    en.wikipedia.org/wiki/Jacobian_matrix_and...

    When this matrix is square, that is, when the function takes the same number of variables as input as the number of vector components of its output, its determinant is referred to as the Jacobian determinant. Both the matrix and (if applicable) the determinant are often referred to simply as the Jacobian in literature. [4]

  4. Kernel (algebra) - Wikipedia

    en.wikipedia.org/wiki/Kernel_(algebra)

    The kernel of a matrix, also called the null space, is the kernel of the linear map defined by the matrix. The kernel of a homomorphism is reduced to 0 (or 1) if and only if the homomorphism is injective, that is if the inverse image of every element consists of a single element. This means that the kernel can be viewed as a measure of the ...

  5. Jacobi method - Wikipedia

    en.wikipedia.org/wiki/Jacobi_method

    The standard convergence condition (for any iterative method) is when the spectral radius of the iteration matrix is less than 1: ((+)) < A sufficient (but not necessary) condition for the method to converge is that the matrix A is strictly or irreducibly diagonally dominant. Strict row diagonal dominance means that for each row, the absolute ...

  6. Positive-definite kernel - Wikipedia

    en.wikipedia.org/wiki/Positive-definite_kernel

    A nonnegative-valued kernel is said to be infinitely divisible if for every there exists a positive-definite kernel such that = (). Another link is that a p.d. kernel induces a pseudometric , where the first constraint on the distance function is loosened to allow d ( x , y ) = 0 {\displaystyle d(x,y)=0} for x ≠ y {\displaystyle x\neq y} .

  7. Kernel smoother - Wikipedia

    en.wikipedia.org/wiki/Kernel_smoother

    Kernel average smoother example. The idea of the kernel average smoother is the following. For each data point X 0, choose a constant distance size λ (kernel radius, or window width for p = 1 dimension), and compute a weighted average for all data points that are closer than to X 0 (the closer to X 0 points get higher weights).

  8. Course Hero buys Symbolab in a rare edtech acquisition

    www.aol.com/news/course-hero-buys-symbolab-rare...

    Months after its $80 million Series B fundraise, Course Hero has acquired Symbolab, an artificial intelligence-powered calculator that helps students answer and understand complex math questions.

  9. Kernel (category theory) - Wikipedia

    en.wikipedia.org/wiki/Kernel_(category_theory)

    As mentioned above, a kernel is a type of binary equaliser, or difference kernel. Conversely, in a preadditive category, every binary equaliser can be constructed as a kernel. To be specific, the equaliser of the morphisms f and g is the kernel of the difference g − f. In symbols: eq (f, g) = ker (g − f).

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