What is the plan along with Optimization.jl, JuMP.jl, Convex.jl, and AD support
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- Dominant language
- Julia
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- 839
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- 100
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Description
Hi, developers!
My question is, is there any plan to support Convex.jl here with AD like cvxpylayers?
For AD of the solution to (convex) optimization problems, I moved to Python and have used cvxpylayers for a while.
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
No files, tests, or entry points are named in the issue. Start by reading the 14-comment discussion and reviewing the existing Convex.jl, JuMP.jl, and AD support before defining the scope; done would require an agreed plan for differentiating through convex optimization solutions.
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Assessment
- Tech stack
- julia, python
- Domain
- backend-api-design, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100