The study of nonlinear eigenvalue problems (NEPs) has matured into a vibrant field at the intersection of numerical analysis, operator theory and applied mathematics. In contrast to the classical ...
Understanding and implementation of algorithms to calculate matrix decompositions such as eigenvalue/vector, LU, QR, and SVD decompositions. Applications include data-fitting, image analysis, and ...
Linear algebra is central to many algorithms in engineering, science, and machine learning; hence, accelerating it would have tremendous economic impact. Quantum computing has been proposed for this ...
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