Class sym::GncOptimizer#
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template<typename BaseOptimizerType>
class GncOptimizer : public BaseOptimizerType# Subclass of Optimizer for using Graduated Non-Convexity (GNC)
Assumes the convexity of the cost function is controlled by a hyperparameter mu. When mu == 0 the cost function should be convex and as mu goes to 1 the cost function should smoothly transition to a robust cost.
Public Types
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using BaseOptimizer = BaseOptimizerType#
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using Scalar = typename BaseOptimizer::Scalar#
Public Functions
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template<typename ...OptimizerArgs>
inline GncOptimizer(const optimizer_params_t &optimizer_params, const optimizer_gnc_params_t &gnc_params, const Key &gnc_mu_key, OptimizerArgs&&... args)# Constructor that copies in factors and keys
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virtual ~GncOptimizer() = default#
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inline void Optimize(Values<Scalar> &values, int num_iterations, bool populate_best_linearization, typename BaseOptimizer::Stats &stats) override#
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using BaseOptimizer = BaseOptimizerType#