A multilevel Monte Carlo estimator for matrix multiplication - Wu, Y; Polydorides, N (Society for Industrial & Applied Mathematics, 2020)
Inspired by recent developments in multilevel Monte Carlo (MLMC) methods and randomized sketching for linear algebra problems, we propose an MLMC estimator for real-time processing of matrix structured random data. Our algorithm is particularly effective in handling high-dimensional inner products and matrix multiplication, and finds applications in computer vision and large-scale supervised learning.