36 #ifndef _KLDUALINFERENCEMETHOD_H_
37 #define _KLDUALINFERENCEMETHOD_H_
89 virtual const char*
get_name()
const {
return "KLDualInferenceMethod"; }
253 bool m_is_dual_valid;
virtual void get_gradient_of_nlml_wrt_parameters(SGVector< float64_t > gradient)
virtual CDualVariationalGaussianLikelihood * get_dual_variational_likelihood() const
virtual const char * get_name() const
The class Labels models labels, i.e. class assignments of objects.
An abstract class of the mean function.
virtual void lbfgs_precompute()
virtual float64_t lbfgs_optimization()
virtual void check_dual_inference(CLikelihoodModel *mod) const
The dual KL approximation inference method class.
virtual void update_chol()
void set_model(CLikelihoodModel *mod)
virtual void get_gradient_of_dual_objective_wrt_parameters(SGVector< float64_t > gradient)
virtual void update_approx_cov()
virtual SGVector< float64_t > get_alpha()
virtual float64_t get_derivative_related_cov(Eigen::MatrixXd eigen_dK)
virtual void update_deriv()
The KL approximation inference method class.
The class Features is the base class of all feature objects.
virtual float64_t get_dual_objective_wrt_parameters()
virtual void update_alpha()
virtual float64_t get_negative_log_marginal_likelihood_helper()
virtual SGVector< float64_t > get_diagonal_vector()
Class that models dual variational likelihood.
The Likelihood model base class.
virtual ~CKLDualInferenceMethod()