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  2. Tensor (machine learning) - Wikipedia

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

    In machine learning, the term tensor informally refers to two different concepts (i) a way of organizing data and (ii) a multilinear (tensor) transformation. 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 ...

  3. Tensor - Wikipedia

    en.wikipedia.org/wiki/Tensor

    For example, a bilinear form is the same thing as a (0, 2)-tensor; an inner product is an example of a (0, 2)-tensor, but not all (0, 2)-tensors are inner products. In the (0, M ) -entry of the table, M denotes the dimensionality of the underlying vector space or manifold because for each dimension of the space, a separate index is needed to ...

  4. List of datasets in computer vision and image processing

    en.wikipedia.org/wiki/List_of_datasets_in...

    THz and thermal video data set This multispectral data set includes terahertz, thermal, visual, near infrared, and three-dimensional videos of objects hidden under people's clothes. 3D lookup tables are provided that allow you to project images onto 3D point clouds. More than 20 videos.

  5. Row- and column-major order - Wikipedia

    en.wikipedia.org/wiki/Row-_and_column-major_order

    Array (data structure) Comparison of programming languages (array) Index origin, another difference between array types across programming languages; Matrix representation; Morton order, another way of mapping multidimensional data to a one-dimensional index, useful in tree data structures; CSR format, a technique for storing sparse matrices in ...

  6. Index notation - Wikipedia

    en.wikipedia.org/wiki/Index_notation

    A vector treated as an array of numbers by writing as a row vector or column vector (whichever is used depends on convenience or context): = (), = Index notation allows indication of the elements of the array by simply writing a i, where the index i is known to run from 1 to n, because of n-dimensions. [1]

  7. Multilinear subspace learning - Wikipedia

    en.wikipedia.org/wiki/Multilinear_subspace_learning

    [6] [7] Here are some examples of data tensors whose observations are vectorized or whose observations are matrices concatenated into data tensor images (2D/3D), video sequences (3D/4D), and hyperspectral cubes (3D/4D). The mapping from a high-dimensional vector space to a set of lower dimensional vector spaces is a multilinear projection. [4]

  8. Array (data type) - Wikipedia

    en.wikipedia.org/wiki/Array_(data_type)

    An array data structure can be mathematically modeled as an abstract data structure (an abstract array) with two operations get(A, I): the data stored in the element of the array A whose indices are the integer tuple I. set(A, I, V): the array that results by setting the value of that element to V. These operations are required to satisfy the ...

  9. Topological data analysis - Wikipedia

    en.wikipedia.org/wiki/Topological_data_analysis

    The circle-valued map might be useful, "persistence theory for circle-valued maps promises to play the role for some vector fields as does the standard persistence theory for scalar fields", as commented in Dan Burghelea et al. [58] The main difference is that Jordan cells (very similar in format to the Jordan blocks in linear algebra) are ...