Ethan Epperly
@ethanepperly
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PhD candidate in applied math @Caltech and @doecsgf fellow interested in computational linear algebra he/him
Pasadena, CA
Joined July 2020
New paper out with Joel Tropp and Robert Webber! In it, we develop a new accelerated version of the randomly pivoted Cholesky algorithm for approximating a psd matrix using a combination of rejection sampling and block computations. Up to 40x faster!
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RT @_kreda_: New preprint with Alice Cortinovis with some of the best (probabilistic) bounds for DEIM et al.
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RT @DynamicsSIAM: Short Stories: "Rational Approximation" (by Lloyd N. Trefethen, in Notices of the @amermathsoc):
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RT @drjingjing2026: 1/3 Today, an anecdote shared by an invited speaker at #NeurIPS2024 left many Chinese scholars, myself included, feelin…
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@ziad_hatab And psd matrices have nonnegative eigenvalues and the determinant is the product of eigenvalues so det(A) >= 0
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RT @jxbz: Flying to Vancouver for neurips today. I'm excited to talk about: - duality theory for deep learning - deep learning's missing ty…
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Did you know that randomized Nyström approximation of A is equivalent to running the randomized SVD on A⁰ᐧ⁵? This and other surprising facts on this week's blog post on the "Gram correspondence"
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RT @haoxuan_steve_c: Unfortunately I have to miss NeurIPS this year (a very last minute decision…) However, my awesome collaborator @Yinuo_…
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RT @ZongyiLiCaltech: #NeurIPS I am on the 2024-25 job market seeking faculty positions and postdocs! My goal is to advance AI for scientifi…
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New blog post up! The randomized Kaczmarz algorithm doesn’t converge for inconsistent systems of linear equations, but—as an estimator for the least-squares solution—it does have an exponentially decreasing bias
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