alpaqa
develop
Nonconvex constrained optimization
|
(Proximable) functions and operators.
Classes | |
struct | L1Norm< Conf, Weight > |
ℓ₁-norm. More... | |
struct | L1NormComplex< Conf, Weight > |
ℓ₁-norm of complex numbers. More... | |
struct | NuclearNorm< Conf, SVD > |
Nuclear norm (ℓ₁-norm of singular values). More... | |
Variables | |
struct alpaqa::prox_fn | prox |
Compute the proximal mapping. | |
struct alpaqa::prox_step_fn | prox_step |
Compute a generalized forward-backward step. | |
struct alpaqa::prox_fn prox |
Compute the proximal mapping.
func | The proximable function | |
[in] | in | Input vector or matrix |
[out] | out | Proximal mapping of |
[in] | γ | Proximal step size |
struct alpaqa::prox_step_fn prox_step |
Compute a generalized forward-backward step.
func | The proximable function | |
[in] | in | Input vector or matrix |
[in] | fwd_step | Step |
[out] | out | Proximal mapping of |
[out] | fb_step | Forward-backward step |
[in] | γ | Proximal step size |
[in] | γ_fwd | Forward step size |
This function can be used to implement the TypeErasedProblem::eval_prox_grad_step function:
Note the negative sign for the forward step size.