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LM: only recompute Jacobian norm if problem is nonlinear#156

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dpo merged 6 commits into
JuliaSmoothOptimizers:masterfrom
MohamedLaghdafHABIBOULLAH:LM-update
Feb 26, 2025
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LM: only recompute Jacobian norm if problem is nonlinear#156
dpo merged 6 commits into
JuliaSmoothOptimizers:masterfrom
MohamedLaghdafHABIBOULLAH:LM-update

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@MohamedLaghdafHABIBOULLAH

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We enable the use of R2DH as a subsolver with different stopping criteria for the subproblem.
Remark: this PR uses the input_struct.jl defined here: #153

@MohamedLaghdafHABIBOULLAH

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@dpo pour cette PR j'ai modifié le critère d'arrêt du sous solveur de LM pour qu'il soit le même que R2N

Comment thread src/LM_alg.jl Outdated
Comment thread src/LM_alg.jl
Comment thread src/LM_alg.jl Outdated
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dpo commented Jan 17, 2025

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@MohamedLaghdafHABIBOULLAH Please rebase and revise this PR.

@MaxenceGollier

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As discussed, I suggest to modify the default value of $$\theta$$ to 1/(1+eps(R)^(1 / 5)) in ROSolverOptions here and change the definition of νInv accordingly (see #172).

@MohamedLaghdafHABIBOULLAH

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As discussed, I suggest to modify the default value of θ to 1/(1+eps(R)^(1 / 5)) in ROSolverOptions here and change the definition of νInv accordingly (see #172).

Done, could you review this PR @MaxenceGollier ?

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Could you also please rename this PR so it has a descriptive title?

Comment thread src/LM_alg.jl Outdated
@MohamedLaghdafHABIBOULLAH MohamedLaghdafHABIBOULLAH changed the title update LM solver LM as R2N, accounting for linearity Feb 26, 2025
@MohamedLaghdafHABIBOULLAH MohamedLaghdafHABIBOULLAH changed the title LM as R2N, accounting for linearity Implementation of LM as R2N while accounting for linearity. Feb 26, 2025
@dpo dpo changed the title Implementation of LM as R2N while accounting for linearity. LM: only recompute Jacobian norm if problem is nonlinear Feb 26, 2025
@dpo dpo added the enhancement New feature or request label Feb 26, 2025
@dpo dpo merged commit 9bc4177 into JuliaSmoothOptimizers:master Feb 26, 2025
@dpo

dpo commented Feb 26, 2025

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Thank you.

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3 participants