*Last updated: 2023-03-16.*

# Module: tf_quant_finance.math.optimizer

View source Optimization methods. ## Classes [`class ConjugateGradientParams`](../../tf_quant_finance/math/optimizer/ConjugateGradientParams.md): Adjustable parameters of conjugate gradient algorithm. ## Functions [`bfgs_minimize(...)`](../../tf_quant_finance/math/optimizer/bfgs_minimize.md): Applies the BFGS algorithm to minimize a differentiable function. [`conjugate_gradient_minimize(...)`](../../tf_quant_finance/math/optimizer/conjugate_gradient_minimize.md): Minimizes a differentiable function. [`converged_all(...)`](../../tf_quant_finance/math/optimizer/converged_all.md): Condition to stop when all batch members have converged or failed. [`converged_any(...)`](../../tf_quant_finance/math/optimizer/converged_any.md): Condition to stop when any batch member converges, or all have failed. [`differential_evolution_minimize(...)`](../../tf_quant_finance/math/optimizer/differential_evolution_minimize.md): Applies the Differential evolution algorithm to minimize a function. [`differential_evolution_one_step(...)`](../../tf_quant_finance/math/optimizer/differential_evolution_one_step.md): Performs one step of the differential evolution algorithm. [`lbfgs_minimize(...)`](../../tf_quant_finance/math/optimizer/lbfgs_minimize.md): Applies the L-BFGS algorithm to minimize a differentiable function. [`nelder_mead_minimize(...)`](../../tf_quant_finance/math/optimizer/nelder_mead_minimize.md): Minimum of the objective function using the Nelder Mead simplex algorithm. [`nelder_mead_one_step(...)`](../../tf_quant_finance/math/optimizer/nelder_mead_one_step.md): A single iteration of the Nelder Mead algorithm.