SHOGUN  6.1.3
KLDualInferenceMethod.h
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3  * Written (w) 2014 Wu Lin
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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 
36 #ifndef _KLDUALINFERENCEMETHOD_H_
37 #define _KLDUALINFERENCEMETHOD_H_
38 
39 #include <shogun/lib/config.h>
43 
44 namespace shogun
45 {
46 
49 {
50 public:
52 
57 
59 
64  virtual float64_t minimize();
65 
66  virtual const char* get_name() const { return "KLDualInferenceMethodMinimizer"; }
67 
68 protected:
70  virtual void init_minimization();
71 
72 private:
76  static float64_t evaluate(void *obj, const float64_t *variable,
77  float64_t *gradient, const int dim, const float64_t step);
78 
84  static float64_t adjust_step(void *obj, const float64_t *parameters,
85  const float64_t *direction, const int dim, const float64_t step);
86 
88  void init() { }
89 };
90 
109 {
110 friend class KLDualInferenceMethodCostFunction;
111 public:
114 
123  CKLDualInferenceMethod(CKernel* kernel, CFeatures* features,
124  CMeanFunction* mean, CLabels* labels, CLikelihoodModel* model);
125 
126  virtual ~CKLDualInferenceMethod();
127 
132  virtual const char* get_name() const { return "KLDualInferenceMethod"; }
133 
138  virtual EInferenceType get_inference_type() const { return INF_KL_DUAL; }
139 
145  static CKLDualInferenceMethod * obtain_from_generic(CInference* inference);
146 
157  virtual SGVector<float64_t> get_alpha();
158 
170  virtual SGVector<float64_t> get_diagonal_vector();
171 
176  void set_model(CLikelihoodModel* mod);
177 
182  virtual void register_minimizer(Minimizer* minimizer);
183 protected:
184 
191 
195  virtual CDualVariationalGaussianLikelihood* get_dual_variational_likelihood() const;
196 
202  virtual void check_dual_inference(CLikelihoodModel* mod) const;
203 
205  virtual void update_approx_cov();
206 
208  virtual void update_alpha();
209 
211  virtual void update_chol();
212 
216  virtual void update_deriv();
217 
223  virtual float64_t get_negative_log_marginal_likelihood_helper();
224 
233  virtual bool precompute();
234 
247  virtual float64_t get_derivative_related_cov(SGMatrix<float64_t> dK);
248 
250  virtual float64_t optimization();
251 
268  virtual float64_t get_dual_objective_wrt_parameters();
269 
285  virtual void get_gradient_of_dual_objective_wrt_parameters(SGVector<float64_t> gradient);
286 
287 private:
288  void init();
289 
291  SGVector<float64_t> m_sW;
292 
297 
301  SGVector<float64_t> m_dv;
302 
304  SGVector<float64_t> m_df;
305 
311 
317  bool m_is_dual_valid;
318 
329 };
330 }
331 #endif /* _KLDUALINFERENCEMETHOD_H_ */
virtual void get_gradient_of_nlml_wrt_parameters(SGVector< float64_t > gradient)
virtual const char * get_name() const
The class Labels models labels, i.e. class assignments of objects.
Definition: Labels.h:43
virtual EInferenceType get_inference_type() const
Build-in minimizer for KLDualInference.
An abstract class of the mean function.
Definition: MeanFunction.h:49
std::enable_if<!std::is_same< T, complex128_t >::value, float64_t >::type mean(const Container< T > &a)
The class wraps the Shogun&#39;s C-style LBFGS minimizer.
CKLDualInferenceMethodMinimizer(FirstOrderCostFunction *fun)
The dual KL approximation inference method class.
The KL approximation inference method class.
Definition: KLInference.h:75
double float64_t
Definition: common.h:60
EInferenceType
Definition: Inference.h:53
The first order cost function base class.
all of classes and functions are contained in the shogun namespace
Definition: class_list.h:18
The Inference Method base class.
Definition: Inference.h:81
virtual const char * get_name() const
The class Features is the base class of all feature objects.
Definition: Features.h:69
The Kernel base class.
The minimizer base class.
Definition: Minimizer.h:43
Class that models dual variational likelihood.
The Likelihood model base class.

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