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...
Egile Nagusiak: | Hu, R, Nicholls, GK, Sejdinovic, D |
---|---|
Formatua: | Journal article |
Hizkuntza: | English |
Argitaratua: |
Springer Nature
2021
|
Antzeko izenburuak
-
Large-scale kernel methods for independence testing
nork: Zhang, Q, et al.
Argitaratua: (2017) -
Large scale methods for kernels, causal inference and survival modelling
nork: Hu, R
Argitaratua: (2022) -
Causal inference via Kernel deviance measures
nork: Mitrovic, J, et al.
Argitaratua: (2018) -
Optimal kernel choice for large-scale two-sample tests
nork: Gretton, A, et al.
Argitaratua: (2012) -
DR-ABC: Approximate Bayesian computation with kernel-based distribution regression
nork: Mitrovic, J, et al.
Argitaratua: (2016)