JuliaFirstOrder / ProximalAlgorithms.jl
Proximal algorithms for nonsmooth optimization in Julia
Why this job: works in the areas we cover, but does not say which job it does
What it does
This package provides algorithms for the minimization of objective functions that include non-smooth terms, such as constraints or non-differentiable penalties. Implemented algorithms include:
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit 25 days ago
- Stars
- 142
- On GitHub
- Licence
- Custom
- Read before business use
- Downloads for
- None listed
- No release files
- Latest version
- v0.7.0
- Released 22 months ago
- Built with
- Julia
- 100% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 68% closed
- 9 still open
- Pull requests
- 68 merged
- 4 waiting
- Releases
- 16
- 0 in the last year
- No contributing guide
- No security policy
- No code of conduct
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More: languages, topics and project record
Languages
- Julia 100%
- Just <1%
Topics
- admm
- julia
- machine-learning
- nonlinear-programming
- nonsmooth-optimization
- numerical-optimization
- optimal-control
- optimization
- optimization-algorithms
- proximal-algorithms
- proximal-gradient-method
- proximal-operators
Project record
- JobOther AI tools
- StatusListed
- Commits187
- Forks26
- Watching8
- Stars in 28 days+1
- CreatedOct 19, 2017
- First seen by usNov 7, 2026
- CheckedNov 8, 2026