Web Reference: Today: Very simple sublinear time algorithm for approximating all eigenvalues of any symmetric bounded entry matrix. Just sample a uniform random principal submatrix and computes its eigenvalues. Improved algorithm for sparse matrices when you can sample rows/columns with probabilities proportional to their sparsity. Feb 12, 2024 · Our goal is to study simple, sampling-based sublinear time algorithms that work under much weaker assumptions on the input matrix. Our main contribution is to show that a very simple algorithm can be used to approximate all eigenvalues of any symmetric matrix with bounded entries. Sep 16, 2021 · We present a simple sublinear time algorithm that approximates all eigenvalues of A up to additive error ±ϵn using those of a randomly sampled O~(log3 n ϵ3) ×O~(log3 n ϵ3) principal submatrix.
YouTube Excerpt: ... McNamara on the work that we did on
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