戚厚铎教授，香港理工大学

Zero-One Composite Optimization (0/1-COP) is a prototype of nonsmooth, non- convex optimization problems and it has attracted much attention recently. Augmented Lagrangian Method (ALM) has stood out as a leading methodology for such problems. The main purpose of this paper is to extend the classical theory of ALM fromsmooth problems to 0/1-COP. We propose, for the first time, second-order optimality conditions for 0/1-COP. In particular, under a second-order sufficient condition (SOSC), we prove Q-linear convergence rate of the proposed ALM. In order to identify the subspace used in SOSC, we employ the proximal operator of the 0/1-loss function, leading to an active-set identification technique. Built around this identification process, we design practical stopping criteria for any algorithm to be used for the subproblem of ALM. We justify that Newton's method is an ideal candidate for the subproblem and it enjoys both global and quadratic convergence. Those considerations result in an inexact Newton ALM (iNALM) for 0/1-COP. The method of iNALM is unique in the sense that it is active-set based, it is inexact (hence more practical), and SOSC instead of widely assumed Kurdyka-Lojasiewicz (KL) properties plays an important in its R-linear convergence analysis. The numerical results on both simulated and real datasets show the fast running speed and high accuracy of iNALM when compared with several leading solvers (Joint work with Xiu Naihua and Zhang Penghe).