3 papers
math.NA2026
Sharp bounds for non-adaptive randomized approximation of high-dimensional noisy vectors
Robert J. Kunsch, Marcin Wnuk
We study the complexity of approximating the finite-dimensional vector space embedding for based on non-adaptive rand…
math.NA2025
Adaptive and non-adaptive randomized approximation of high-dimensional vectors
Robert J. Kunsch, Marcin Wnuk
We study approximation of the embedding , , based on randomized algorithms that use up to arbitrary linear function…
math.NA2025
Data Compression using Rank-1 Lattices for Parameter Estimation in Machine Learning
Michael Gnewuch, Kumar Harsha, Marcin Wnuk
The mean squared error and regularized versions of it are standard loss functions in supervised machine learning. However, calculating these losses for large data sets can be compu…