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Publications associées (5)
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Quantum computing has received wide-spread attention lately due the possibility of a near-term breakthrough of quantum supremacy. This course acts as an introduction to the area of quantum computing.
We describe a randomized algorithm for producing a near-optimal hierarchical off-diagonal low-rank (HODLR) approximation to an n × n matrix A, accessible only though matrix-vector products with A and AT. We prove that, for the rank-k HODLR approximation pr ...
Society for Industrial and Applied Mathematics2025
Low-rank approximation of a matrix function, f(A), is an important task in computational mathematics. Most methods require direct access to f(A), which is often considerably more expensive than accessing A. Persson and Kressner [SIAM J. Matrix Anal., 44 (2 ...
In this thesis we will present and analyze randomized algorithms for numerical linear algebra problems. An important theme in this thesis is randomized low-rank approximation. In particular, we will study randomized low-rank approximation of matrix functio ...