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# StructuredOptimization.jl
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[![](https://img.shields.io/badge/docs-stable-blue.svg)](https://kul-optec.github.io/StructuredOptimization.jl/stable)
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[![](https://img.shields.io/badge/docs-latest-blue.svg)](https://kul-optec.github.io/StructuredOptimization.jl/latest)
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[![](https://img.shields.io/badge/docs-stable-blue.svg)](https://juliafirstorder.github.io/StructuredOptimization.jl/stable)
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[![](https://img.shields.io/badge/docs-latest-blue.svg)](https://juliafirstorder.github.io/StructuredOptimization.jl/latest)
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StructuredOptimization.jl is a high-level modeling language
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that utilizes a syntax that is very close to
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acts as a parser to utilize
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three different packages:
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* [ProximalOperators.jl](https://github.com/kul-optec/ProximalOperators.jl)
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* [ProximalOperators.jl](https://github.com/JuliaFirstOrder/ProximalOperators.jl)
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* [AbstractOperators.jl](https://github.com/kul-optec/AbstractOperators.jl)
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* [ProximalAlgorithms.jl](https://github.com/kul-optec/ProximalAlgorithms.jl)
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* [ProximalAlgorithms.jl](https://github.com/JuliaFirstOrder/ProximalAlgorithms.jl)
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StructuredOptimization.jl can handle large-scale convex and nonconvex problems with nonsmooth cost functions.
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[...]
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```
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See the [documentation](https://kul-optec.github.io/StructuredOptimization.jl/latest) for more details about the type of problems StructuredOptimization.jl can handle and the [demos](https://kul-optec.github.io/StructuredOptimization.jl/stable/demos/) to check out some examples.
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See the [documentation](https://juliafirstorder.github.io/StructuredOptimization.jl/latest) for more details about the type of problems StructuredOptimization.jl can handle and the [demos](https://juliafirstorder.github.io/StructuredOptimization.jl/stable/demos/) to check out some examples.

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