1 citations · 1 across the 4 of their papers we have counts for
4 papers
Expected extremal area of facets of random polytopes
Brett Leroux, Luis Rademacher, Carsten Schütt +1
We study extremal properties of spherical random polytopes, the convex hull of random points chosen from the unit Euclidean sphere in . The extremal properties of int…
Euclidean distance compression via deep random features
Brett Leroux, Luis Rademacher
Motivated by the problem of compressing point sets into as few bits as possible while maintaining information about approximate distances between points, we construct random nonlin…
On the Nystrom Approximation for Preconditioning in Kernel Machines
Amirhesam Abedsoltan, Parthe Pandit, Luis Rademacher +1
Kernel methods are a popular class of nonlinear predictive models in machine learning. Scalable algorithms for learning kernel models need to be iterative in nature, but convergenc…
The Minimum Euclidean-Norm Point on a Convex Polytope: Wolfe's Combinatorial Algorithm is Exponential
Jesus De Loera, Jamie Haddock, Luis Rademacher
The complexity of Philip Wolfe's method for the minimum Euclidean-norm point problem over a convex polytope has remained unknown since he proposed the method in 1974. The method is…