patrick-kidger / patrick-kidger/optimistix
Least squares performance
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question
- Dominant language
- Python
- Stars
- 623
- Forks
- 54
- PR merge metrics
- No merged PRs in 30d
Description
Hi Patrick, I see you are using general solvers to solve the least squares problem, by contructing an objective out of residuals. I have found this approach is less performant than using Levenberg Marquardt. Do you get good performance?
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Research direction
Start in optimistix/_least_squares.py at line 43, then compare the current residual-objective approach with the proposed Levenberg–Marquardt approach. Before coding, establish the expected performance comparison; done should be a decided, documented approach or a concrete LM implementation with evidence that it improves least-squares performance.
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Assessment
- Tech stack
- python
- Domain
- performance
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100