SHOGUN  6.1.3
DualVariationalGaussianLikelihood.h
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30  * the reference paper is
31  * Mohammad Emtiyaz Khan, Aleksandr Y. Aravkin, Michael P. Friedlander, Matthias Seeger
32  * Fast Dual Variational Inference for Non-Conjugate Latent Gaussian Models. ICML2013
33  */
34 
35 #ifndef _DUALVARIATIONALGAUSSIANLIKELIHOOD_H_
36 #define _DUALVARIATIONALGAUSSIANLIKELIHOOD_H_
37 
38 #include <shogun/lib/config.h>
39 
41 
42 namespace shogun
43 {
63 {
64 public:
67 
69 
74  virtual const char* get_name() const { return "DualVariationalGaussianLikelihood"; }
75 
82 
91 
98  virtual bool supports_derivative_wrt_hyperparameter() const;
99 
109 
121  SGVector<float64_t> s2, const CLabels* lab);
122 
127  virtual bool dual_parameters_valid() const;
128 
139  virtual float64_t adjust_step_wrt_dual_parameter(SGVector<float64_t> direction, const float64_t step) const;
140 
149  virtual void set_dual_parameters(SGVector<float64_t> the_lambda, const CLabels* lab);
150 
155  virtual SGVector<float64_t> get_mu_dual_parameter() const=0;
156 
162 
167  virtual float64_t get_dual_upper_bound() const=0;
168 
173  virtual float64_t get_dual_lower_bound() const=0;
174 
179  virtual bool dual_upper_bound_strict() const=0;
180 
185  virtual bool dual_lower_bound_strict() const=0;
186 
192 
199  virtual SGVector<float64_t> get_dual_first_derivative(const TParameter* param) const=0;
200 
206  virtual void set_strict_scale(float64_t strict_scale);
207 
208 
216  virtual void set_noise_factor(float64_t noise_factor);
217 protected:
218 
227 
235 
238 
243  virtual void precompute();
244 
249 private:
251  void init();
252 
253 };
254 }
255 #endif /* _DUALVARIATIONALGAUSSIANLIKELIHOOD_H_ */
virtual SGVector< float64_t > get_first_derivative_wrt_hyperparameter(const TParameter *param) const
virtual void set_dual_parameters(SGVector< float64_t > the_lambda, const CLabels *lab)
virtual SGVector< float64_t > get_mu_dual_parameter() const =0
The class Labels models labels, i.e. class assignments of objects.
Definition: Labels.h:43
virtual bool dual_lower_bound_strict() const =0
The variational Gaussian Likelihood base class. The variational distribution is Gaussian.
parameter struct
virtual SGVector< float64_t > get_dual_objective_value()=0
virtual float64_t get_dual_upper_bound() const =0
virtual float64_t adjust_step_wrt_dual_parameter(SGVector< float64_t > direction, const float64_t step) const
double float64_t
Definition: common.h:60
virtual bool set_variational_distribution(SGVector< float64_t > mu, SGVector< float64_t > s2, const CLabels *lab)
virtual SGVector< float64_t > get_variance_dual_parameter() const =0
virtual SGVector< float64_t > get_dual_first_derivative(const TParameter *param) const =0
virtual CVariationalGaussianLikelihood * get_variational_likelihood() const
virtual float64_t get_dual_lower_bound() const =0
all of classes and functions are contained in the shogun namespace
Definition: class_list.h:18
virtual bool dual_upper_bound_strict() const =0
virtual SGVector< float64_t > get_variational_first_derivative(const TParameter *param) const
Class that models dual variational likelihood.

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