(Nonlinear) Optimization Functions#

The implementation for solver

\[\arg\min_{\theta \in R^s} f(\theta),\]

where

  • \(\theta\) is a \(s\)-dimensional parameter vector (note that \(s\) is the desired sparsity in sparsity-constraint optimization)

  • \(f(\theta)\) is the objective function.

Functions#

convex_solver_LBFGS(objective_func, value_and_grad, ...)

skscope.numeric_solver.convex_solver_BFGS(objective_func, value_and_grad, init_params, optim_variable_set, data)[source]#
skscope.numeric_solver.convex_solver_LBFGS(objective_func, value_and_grad, init_params, optim_variable_set, data)[source]#