Add spectral methods for HMM learning
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- Dominant language
- Python
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Description
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
@JeanKossaifi, it sounds like you may have some code for this in Tensorly?
Thanks @Anima-Lab for suggesting this!
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
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Research direction
Start by reviewing the repository's existing HMM learning implementations for SGD and EM, then read the linked Tensorly project and Anandkumar et al. paper for the proposed spectral approach. Determine which spectral methods and interfaces should be supported and how they should be validated. Done means spectral learning is integrated alongside the existing learning methods with appropriate tests.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100