1 code implementation • 11 Sep 2023 • Frederiek Wesel, Kim Batselier
Unless one considers the dual formulation of the learning problem, which renders exact large-scale learning unfeasible, the exponential increase of model parameters in the dimensionality of the data caused by their tensor-product structure prohibits to tackle high-dimensional problems.
no code implementations • 25 May 2022 • Eva Memmel, Clara Menzen, Jetze Schuurmans, Frederiek Wesel, Kim Batselier
Furthermore, we argue that better algorithms should be evaluated in terms of both accuracy and efficiency.
1 code implementation • NeurIPS 2021 • Frederiek Wesel, Kim Batselier
Random Fourier features provide a way to tackle large-scale machine learning problems with kernel methods.