Struct argmin::solver::conjugategradient::nonlinear_cg::NonlinearConjugateGradient [−][src]
pub struct NonlinearConjugateGradient<P, L, B, F> { /* fields omitted */ }
Expand description
The nonlinear conjugate gradient is a generalization of the conjugate gradient method for nonlinear optimization problems.
References:
[0] Jorge Nocedal and Stephen J. Wright (2006). Numerical Optimization. Springer. ISBN 0-387-30303-0.
Implementations
Constructor (Polak Ribiere Conjugate Gradient (PR-CG))
Specifiy the number of iterations after which a restart should be performed This allows the algorithm to “forget” previous information which may not be helpful anymore.
Set the value for the orthogonality measure. Setting this parameter leads to a restart of the algorithm (setting beta = 0) after two consecutive search directions are not orthogonal anymore. In other words, if this condition is met:
|\nabla f_k^T * \nabla f_{k-1}| / | \nabla f_k ||^2 >= v
A typical value for v
is 0.1.
Trait Implementations
impl<'de, P, L, B, F> Deserialize<'de> for NonlinearConjugateGradient<P, L, B, F> where
P: Deserialize<'de>,
L: Deserialize<'de>,
B: Deserialize<'de>,
F: Deserialize<'de>,
impl<'de, P, L, B, F> Deserialize<'de> for NonlinearConjugateGradient<P, L, B, F> where
P: Deserialize<'de>,
L: Deserialize<'de>,
B: Deserialize<'de>,
F: Deserialize<'de>,
fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
__D: Deserializer<'de>,
fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
__D: Deserializer<'de>,
Deserialize this value from the given Serde deserializer. Read more
impl<O, P, L, B, F> Solver<O> for NonlinearConjugateGradient<P, L, B, F> where
O: ArgminOp<Param = P, Output = F, Float = F>,
P: Clone + Default + Serialize + DeserializeOwned + ArgminSub<O::Param, O::Param> + ArgminDot<O::Param, O::Float> + ArgminScaledAdd<O::Param, O::Float, O::Param> + ArgminAdd<O::Param, O::Param> + ArgminMul<F, O::Param> + ArgminNorm<O::Float>,
O::Hessian: Default,
L: Clone + ArgminLineSearch<O::Param, O::Float> + Solver<OpWrapper<O>>,
B: ArgminNLCGBetaUpdate<O::Param, O::Float>,
F: ArgminFloat,
impl<O, P, L, B, F> Solver<O> for NonlinearConjugateGradient<P, L, B, F> where
O: ArgminOp<Param = P, Output = F, Float = F>,
P: Clone + Default + Serialize + DeserializeOwned + ArgminSub<O::Param, O::Param> + ArgminDot<O::Param, O::Float> + ArgminScaledAdd<O::Param, O::Float, O::Param> + ArgminAdd<O::Param, O::Param> + ArgminMul<F, O::Param> + ArgminNorm<O::Float>,
O::Hessian: Default,
L: Clone + ArgminLineSearch<O::Param, O::Float> + Solver<OpWrapper<O>>,
B: ArgminNLCGBetaUpdate<O::Param, O::Float>,
F: ArgminFloat,
Auto Trait Implementations
impl<P, L, B, F> RefUnwindSafe for NonlinearConjugateGradient<P, L, B, F> where
B: RefUnwindSafe,
F: RefUnwindSafe,
L: RefUnwindSafe,
P: RefUnwindSafe,
impl<P, L, B, F> Send for NonlinearConjugateGradient<P, L, B, F> where
B: Send,
F: Send,
L: Send,
P: Send,
impl<P, L, B, F> Sync for NonlinearConjugateGradient<P, L, B, F> where
B: Sync,
F: Sync,
L: Sync,
P: Sync,
impl<P, L, B, F> Unpin for NonlinearConjugateGradient<P, L, B, F> where
B: Unpin,
F: Unpin,
L: Unpin,
P: Unpin,
impl<P, L, B, F> UnwindSafe for NonlinearConjugateGradient<P, L, B, F> where
B: UnwindSafe,
F: UnwindSafe,
L: UnwindSafe,
P: UnwindSafe,
Blanket Implementations
Mutably borrows from an owned value. Read more
pub fn vzip(self) -> V