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  2. Kernel (image processing) - Wikipedia

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

    For example, if we have two three-by-three matrices, the first a kernel, and the second an image piece, convolution is the process of flipping both the rows and columns of the kernel and multiplying locally similar entries and summing.

  3. Convolution - Wikipedia

    en.wikipedia.org/wiki/Convolution

    The convolution of two finite sequences is defined by extending the sequences to finitely supported functions on the set of integers. When the sequences are the coefficients of two polynomials, then the coefficients of the ordinary product of the two polynomials are the convolution of the original two

  4. Tensor contraction - Wikipedia

    en.wikipedia.org/wiki/Tensor_contraction

    [2] [3] Applying the canonical pairing to the kth V factor and the lth V ∗ factor, and using the identity on all other factors, defines the (k, l) contraction operation, which is a linear map that yields a tensor of type (m − 1, n − 1). [2] By analogy with the (1, 1) case, the general contraction operation is sometimes called the trace.

  5. Tensor decomposition - Wikipedia

    en.wikipedia.org/wiki/Tensor_decomposition

    A multi-way graph with K perspectives is a collection of K matrices ,..... with dimensions I × J (where I, J are the number of nodes). This collection of matrices is naturally represented as a tensor X of size I × J × K. In order to avoid overloading the term “dimension”, we call an I × J × K tensor a three “mode” tensor, where “modes” are the numbers of indices used to index ...

  6. Tensor (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Tensor_(machine_learning)

    In machine learning, the term tensor informally refers to two different concepts for organizing and representing data. Data may be organized in a multidimensional array (M-way array), informally referred to as a "data tensor"; however, in the strict mathematical sense, a tensor is a multilinear mapping over a set of domain vector spaces to a range vector space.

  7. Matrix multiplication algorithm - Wikipedia

    en.wikipedia.org/wiki/Matrix_multiplication...

    The definition of matrix multiplication is that if C = AB for an n × m matrix A and an m × p matrix B, then C is an n × p matrix with entries = =. From this, a simple algorithm can be constructed which loops over the indices i from 1 through n and j from 1 through p, computing the above using a nested loop:

  8. Download, install, or uninstall AOL Desktop Gold - AOL Help

    help.aol.com/articles/aol-desktop-downloading...

    2. Open the email. 3. Click Download AOL Desktop Gold or Update Now. 4. Navigate to your Downloads folder and click Save. 5. Follow the installation steps listed ...

  9. Matrix mortality problem - Wikipedia

    en.wikipedia.org/wiki/Matrix_mortality_problem

    In fact, it is already undecidable for sets of 6 matrices (or more) when n = 3, for 4 matrices when n = 5, for 3 matrices when n = 9, and for 2 matrices when n = 15 [2]. In the case n = 2, it is an open problem whether matrix mortality is decidable, but several special cases have been solved: the problem is decidable for sets of 2 matrices [ 3 ...

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    2d convolution matrix exampletensor contraction formula