Search Results for author: Frederiek Wesel

Found 3 papers, 2 papers with code

Quantized Fourier and Polynomial Features for more Expressive Tensor Network Models

1 code implementation11 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.

Quantization

Large-Scale Learning with Fourier Features and Tensor Decompositions

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.

Tensor Decomposition

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