patrick-kidger / patrick-kidger/optimistix
Implement `NonlinearCG` variant which uses memoryless BFGS update
Open
Nobody has claimed this yet.
feature
- Dominant language
- Python
- Stars
- 623
- Forks
- 54
- PR merge metrics
- No merged PRs in 30d
Description
This would allow us to use all our line searches and descents with the nonlinear CG approximate Hessian. See Conjugate Gradient Methods with Inexact Line Search by Shanno.
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.
- Open a pull request that references the issue number.
Research direction
Start by reading the linked paper, “Conjugate Gradient Methods with Inexact Line Search,” then inspect the existing line searches and descents that the issue says should work with the new variant. Compare the requested memoryless BFGS update with the current nonlinear CG approach; done means a NonlinearCG variant supports those existing line searches and descents.
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
- Mostly clear
- Newbie friendliness
- 25/100