Compute the expectation:
    expectation[n] = <m(x_n)^T K_{x_n, Z}>_p(x_n)
        - m(x_i) = c :: Constant function
        - K_{.,.}    :: Kernel function

    :return: NxQxM

def _expectation(p, constant_mean, none, kern, feat, nghp=None):
    """
    Compute the expectation:
    expectation[n] = <m(x_n)^T K_{x_n, Z}>_p(x_n)
        - m(x_i) = c :: Constant function
        - K_{.,.}    :: Kernel function

    :return: NxQxM
    """
    with params_as_tensors_for(constant_mean):
        c = constant_mean(p.mu)  # NxQ
        eKxz = expectation(p, (kern, feat), nghp=nghp)  # NxM

        return c[..., None] * eKxz[:, None, :]