Large scale tensor regression using kernels and variational inference
We outline an inherent flaw of tensor factorization models when latent factors are expressed as a function of side information and propose a novel method to mitigate this. We coin our methodology Kernel Fried Tensor (KFT) and present it as a large-scale prediction and forecasting tool for high dimen...
| Главные авторы: | , , |
|---|---|
| Формат: | Journal article |
| Язык: | English |
| Опубликовано: |
Springer Nature
2021
|