SingleFITCInference.h

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/*
 * Copyright (c) The Shogun Machine Learning Toolbox
 * Written (W) 2015 Wu Lin
 * All rights reserved.
 *
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions are met:
 *
 * 1. Redistributions of source code must retain the above copyright notice, this
 *    list of conditions and the following disclaimer.
 * 2. Redistributions in binary form must reproduce the above copyright notice,
 *    this list of conditions and the following disclaimer in the documentation
 *    and/or other materials provided with the distribution.
 *
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
 * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
 * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
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 */

#ifndef CSINGLEFITCINFERENCE_H
#define CSINGLEFITCINFERENCE_H


#include <shogun/lib/config.h>
#include <shogun/machine/gp/SingleSparseInference.h>
#include <shogun/lib/Lock.h>

namespace shogun
{

class CSingleFITCInference: public CSingleSparseInference
{
public:
    CSingleFITCInference();

    CSingleFITCInference(CKernel* kernel, CFeatures* features,
            CMeanFunction* mean, CLabels* labels, CLikelihoodModel* model,
            CFeatures* inducing_features);

    virtual ~CSingleFITCInference();

    virtual const char* get_name() const { return "SingleFITCInference"; }

protected:

    virtual float64_t get_derivative_related_cov(SGVector<float64_t> ddiagKi,
        SGMatrix<float64_t> dKuui, SGMatrix<float64_t> dKui);

    virtual float64_t get_derivative_related_cov(SGVector<float64_t> ddiagKi,
        SGMatrix<float64_t> dKuui, SGMatrix<float64_t> dKui,
        SGVector<float64_t> v, SGMatrix<float64_t> R);

    virtual float64_t get_derivative_related_cov_helper(SGMatrix<float64_t> dKuui,
        SGVector<float64_t> v, SGMatrix<float64_t> R);

    virtual SGVector<float64_t> get_derivative_wrt_inducing_noise(
        const TParameter* param);

    virtual SGVector<float64_t> get_derivative_related_cov_diagonal();

    virtual float64_t get_derivative_related_mean(SGVector<float64_t> dmu);

    virtual SGVector<float64_t> get_derivative_related_inducing_features(
    SGMatrix<float64_t> BdK, const TParameter* param);

    virtual void update_alpha()=0;

    virtual void update_chol()=0;

    virtual void update_deriv()=0;

    virtual SGVector<float64_t> get_derivative_wrt_likelihood_model(
            const TParameter* param)=0;

    virtual SGVector<float64_t> get_derivative_wrt_mean(
            const TParameter* param);

    virtual SGVector<float64_t> get_derivative_wrt_inducing_features(const TParameter* param);

    SGVector<float64_t> m_al;

    SGVector<float64_t> m_t;

    SGMatrix<float64_t> m_B;

    SGVector<float64_t> m_w;

    SGMatrix<float64_t> m_Rvdd;

    SGMatrix<float64_t> m_V;

private:
    /* init */
    void init();
};
}
#endif /* CSINGLEFITCINFERENCE_H */