Large-Scale Learning with Fourier Features and Tensor Decompositions F Wesel, K Batselier Advances in Neural Information Processing Systems 34, 17543-17554, 2021 | 15 | 2021 |
Tensor-based Kernel Machines with Structured Inducing Points for Large and High-Dimensional Data F Wesel, K Batselier International Conference on Artificial Intelligence and Statistics, 8308-8320, 2023 | 5 | 2023 |
Position: Tensor Networks are a Valuable Asset for Green AI E Memmel, C Menzen, J Schuurmans, F Wesel, K Batselier Proceedings of Machine Learning Research 235, 35340-35353, 2024 | 4* | 2024 |
Quantized Fourier and Polynomial Features for more Expressive Tensor Network Models F Wesel, K Batselier International Conference on Artificial Intelligence and Statistics, 1261-1269, 2024 | 2 | 2024 |
A Kernelizable Primal-Dual Formulation of the Multilinear Singular Value Decomposition F Wesel, K Batselier arXiv preprint arXiv:2410.10504, 2024 | | 2024 |
Efficient Patient Fine-Tuned Seizure Detection with a Tensor Kernel Machine SJS De Rooij, F Wesel, B Hunyadi 2024 32nd European Signal Processing Conference (EUSIPCO), 1372-1376, 2024 | | 2024 |
Exploiting Hankel-Toeplitz Structures for Fast Computation of Kernel Precision Matrices F Viset, A Kullberg, F Wesel, A Solin arXiv preprint arXiv:2408.02346, 2024 | | 2024 |
Tensor Network-Constrained Kernel Machines as Gaussian Processes F Wesel, K Batselier arXiv preprint arXiv:2403.19500, 2024 | | 2024 |