Code, Data and Results for Numerical Experiments in "Efficient Sketching-Based Summation of Tucker Tensors"
Code, Data and Results for Numerical Experiments in "Efficient Sketching-Based Summation of Tucker Tensors"
This archive contains the companion codes, used data and computed results for the paper: R. Smith, M. Pasha, A. Galindo-Olarte, H. Al Daas, G. Ballard, J. Qiu, J. Nakao, W. Taitano; "Efficient Sketching-Based Summation of Tucker Tensors", which implement numerical experiments for the efficient sketching-based summation of Tucker tenors using Kronecker and Khatri-Rao sketching (reusing factors) with a heuristic subrank selection.
- Wake Forest University United States
- Virginia Tech United States
- Science and Technology Facilities Council United Kingdom
- Rutherford Appleton Laboratory United Kingdom
- The University of Texas at Austin United States
Tucker GMRES, MATLAB, High Dimensional PDEs, Randomized Numerical Linear Algebra, Kronecker Sketching, Low-rank Approximation, Tucker Tensors, Khatri-Rao Sketching, Compressed Summation
Tucker GMRES, MATLAB, High Dimensional PDEs, Randomized Numerical Linear Algebra, Kronecker Sketching, Low-rank Approximation, Tucker Tensors, Khatri-Rao Sketching, Compressed Summation
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