Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on an implementation of the technique that emphasizes simplicity and ease-of-modification over robustness and ...
A collection of differentiable SVD methods and ICCV21 "Why Approximate Matrix Square Root Outperforms Accurate SVD in Global Covariance Pooling?" ...
Abstract: Based on the Xilinx Zynq-7000 platform and the Vivado SDK toolbox, the C model of the matrix SVD decomposition module is established, and the writing, compiling and debugging of the matrix ...
Standard tools like Singular Value Decomposition (SVD) are great for reducing data dimensionality, but their results can be hard to interpret. SVD creates "eigen-frames"—abstract, ghostly patterns ...
Abstract: The element-wise functions of a matrix are widely used in machine learning. For the applications with large matrices, efficiently computing the matrix-vector multiplication of matrix element ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback