You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
In addition to SGD and EM, we should support spectral learning methods. See for example,
Anandkumar, Animashree, et al. "Tensor decompositions for learning latent variable models." Journal of machine learning research 15 (2014): 2773-2832. link
TensorLy does provide all tools for tensor learning (including tensor decomposition) and is backend agnostic (and tested with JAX) so will also work transparently with dynamax. We will also be adding Tensor LDA soon.
I didn't realize TensorLy worked on JAX — cool! I am most familiar with the tensor decomposition approach described in the paper above, but to be honest I need to dig into the details. It's been many years, but I remember liking this short note too: https://arxiv.org/pdf/1204.2477.pdf. Any suggestions welcome.
In addition to SGD and EM, we should support spectral learning methods. See for example,
@JeanKossaifi, it sounds like you may have some code for this in Tensorly?
Thanks @Anima-Lab for suggesting this!
The text was updated successfully, but these errors were encountered: