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Description

Added penalty parameter variable for linearized/proximal ADMM and adaptive penalty parameter method. Can be utilized for fast solves of constrained optimization problems with simple proximal, ie can solve TV problems faster base PDHG.

#2264

Example Usage

     alpha = 1
    K = alpha*GradientOperator(ig)
    G = MixedL21Norm()
    F = L2NormSquared(b = noisy_data)
    num_iters = 100

    admm = LADMM(f = F, g = G, operator = K, rho = 1e0, mode = 'adaptive')
    admm.run(num_iters)

Contribution Notes

  • The content of this Pull Request (the Contribution) is intentionally submitted for inclusion in CIL (the Work) under the terms and conditions of the Apache-2.0 License
  • I confirm that the contribution does not violate any intellectual property rights of third parties

❤️ Thanks for your contribution!

@github-project-automation github-project-automation bot moved this to Todo in UM 2026 Jan 30, 2026
@gfardell gfardell added the community-contribution Community-submitted pull requests from contributors outside the core team. label Jan 30, 2026
@casperdcl casperdcl moved this from Todo to In Progress in UM 2026 Jan 30, 2026
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2 participants