Abstract: Convolution neural networks (CNNs) have been extensively used in machine learning applications. The most time-consuming part of CNNs are convolution operations. A common approach to ...
Abstract: Convolutional neural networks (CNNs) have emerged as one of the most successful machine learning technologies for image and video processing. The most computationally-intensive parts of CNNs ...
Implicit GEMM is the formulation of a convolution operation as a GEMM (generalized matrix-matrix product). Convolution takes an activation tensor and applies a sliding filter on it to produce an ...
SIAM Journal on Applied Mathematics, Vol. 42, No. 5 (Oct., 1982), pp. 941-955 (15 pages) Slepian, Landau and Pollak found that a certain finite convolution integral operator on the real line commutes ...
In electromagnetic transient (EMT) simulations for power systems and inverter-based resources (IBRs), the arrangement of states within the system's linear equations, represented by matrix A in Ax=b, ...
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