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A convergence frame for inexact nonconvex and nonsmooth algorithms and its applications to several iterations

Sun Tao(nudtsuntao***at***163.com)
Jiang Hao(haojiang***at***nudt.edu.cn)
Cheng Lizhi(clzcheng***at***nudt.edu.cn)
Zhu Wei(zhuwei***at***xtu.edu.cn)

Abstract: In this paper, we consider the convergence of an abstract inexact nonconvex and nonsmooth algorithm. We promise a pseudo sufficient descent condition and a pseudo relative error condition, which both are related to an auxiliary sequence, for the algorithm; and a continuity condition is assumed to hold. In fact, a wide of classical inexact nonconvex and nonsmooth algorithms allow these three conditions. Under the finite energy assumption on the auxiliary sequence, we prove the sequence generated by the general algorithm converges to a critical point of the objective function if being assumed Kurdyka-? Lojasiewicz property. The core of the proofs lies on building a new Lyapunov function, whose successive difference provides a bound for the successive difference of the points generated by the algorithm. And then, we apply our findings to several classical nonconvex iterative algorithms and derive corresponding convergence results.

Keywords: Nonconvex minimization; Inexact algorithms; Semi-algebraic functions; Kurdyka-Lojasiewicz property; Convergence analysis

Category 1: Nonlinear Optimization

Citation:

Download: [PDF]

Entry Submitted: 09/18/2017
Entry Accepted: 09/18/2017
Entry Last Modified: 09/18/2017

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