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Copy file name to clipboardExpand all lines: src/R2N.jl
+6-6Lines changed: 6 additions & 6 deletions
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@@ -134,7 +134,7 @@ For advanced usage, first define a solver "R2NSolver" to preallocate the memory
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- `γ::T = T(3)`: regularization parameter multiplier, σ := σ/γ when the iteration is very successful and σ := σγ when the iteration is unsuccessful;
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- `θ::T = 1/(1 + eps(T)^(1 / 5))`: is the model decrease fraction with respect to the decrease of the Cauchy model;
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- `m_monotone::Int = 1`: monotonicity parameter. By default, R2N is monotone but the non-monotone variant will be used if `m_monotone > 1`;
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- `sub_kwargs::Dict{Symbol}`: a dictionary containing the keyword arguments to be sent to the subsolver. The solver will fail if invalid keyword arguments are provided to the subsolver.
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- `sub_kwargs::NamedTuple`: a named tuple containing the keyword arguments to be sent to the subsolver. The solver will fail if invalid keyword arguments are provided to the subsolver.
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The algorithm stops either when `√(ξₖ/νₖ) < atol + rtol*√(ξ₀/ν₀) ` or `ξₖ < 0` and `√(-ξₖ/νₖ) < neg_tol` where ξₖ := f(xₖ) + h(xₖ) - φ(sₖ; xₖ) - ψ(sₖ; xₖ), and √(ξₖ/νₖ) is a stationarity measure.
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