Convergence analysis of stochastic higher-order majorization–minimization algorithms
Convergence analysis of stochastic higher-order majorization–minimization algorithms
AbstractMajorization–minimization schemes are a broad class of iterative methods targeting general optimization problems, including nonconvex, nonsmooth and stochastic. These algorithms minimize successively a sequence of upper bounds of the objective function so that along the iterations the objective value decreases. We present a stochastic higher-order algorithmic framework for minimizing the …