28 citations · 30 across the 6 of their papers we have counts for
6 papers
Interpolation in Polynomial Spaces of p-Degree
Phil-Alexander Hofmann, Damar Wicaksono, Michael Hecht
We recently introduced the Fast Newton Transform (FNT), an hierarchical algorithm for performing multivariate Newton interpolation in arbitrary downward closed polynomial spaces of…
Multivariate Newton Interpolation in Downward Closed Spaces Reaches the Optimal Geometric Approximation Rates for Bos--Levenberg--Trefethen Functions
Michael Hecht, Phil-Alexander Hofmann, Damar Wicaksono +5
We extend the univariate Newton interpolation algorithm to arbitrary spatial dimensions and for any choice of downward-closed polynomial space, while preserving its quadratic runti…
PMBO: Enhancing Black-Box Optimization through Multivariate Polynomial Surrogates
Janina Schreiber, Pau Batlle, Damar Wicaksono +1
We introduce a surrogate-based black-box optimization method, termed Polynomial-model-based optimization (PMBO). The algorithm alternates polynomial approximation with Bayesian opt…
Polynomial-Model-Based Optimization for Blackbox Objectives
Janina Schreiber, Damar Wicaksono, Michael Hecht
For a wide range of applications the structure of systems like Neural Networks or complex simulations, is unknown and approximation is costly or even impossible. Black-box optimiza…
Extraction of the frequency moments of spectral densities from imaginary-time correlation function data
Tobias Dornheim, Damar C. Wicaksono, Juan E. Suarez-Cardona +5
We introduce an exact framework to compute the positive frequency moments of different dynamic properties from imaginary-time quantum Monte Carlo…
Multivariate Polynomial Regression of Euclidean Degree Extends the Stability for Fast Approximations of Trefethen Functions
Sachin K. Thekke Veettil, Yuxi Zheng, Uwe Hernandez Acosta +2
We address classic multivariate polynomial regression tasks from a novel perspective resting on the notion of general polynomial -degree, with total, Euclidean, and maximum de…