The fire distribution can be divided into weapon assignment and firing time scheduling. The criterion of weapon allocation is that a target with greater threat has higher priority. And the criterion of firing time sch...The fire distribution can be divided into weapon assignment and firing time scheduling. The criterion of weapon allocation is that a target with greater threat has higher priority. And the criterion of firing time scheduling is that a target can be damaged with the expected probability before a specific time. A fire distribution scheme and a program for the integrated missile-gun air defense system based on a criterion of earlier damage were presented. An example was taken to illustrate its effectiveness.展开更多
Alternating direction method of multipliers(ADMM)receives much attention in the recent years due to various demands from machine learning and big data related optimization.In 2013,Ouyang et al.extend the ADMM to the s...Alternating direction method of multipliers(ADMM)receives much attention in the recent years due to various demands from machine learning and big data related optimization.In 2013,Ouyang et al.extend the ADMM to the stochastic setting for solving some stochastic optimization problems,inspired by the structural risk minimization principle.In this paper,we consider a stochastic variant of symmetric ADMM,named symmetric stochastic linearized ADMM(SSL-ADMM).In particular,using the framework of variational inequality,we analyze the convergence properties of SSL-ADMM.Moreover,we show that,with high probability,SSL-ADMM has O((ln N)·N^(-1/2))constraint violation bound and objective error bound for convex problems,and has O((ln N)^(2)·N^(-1))constraint violation bound and objective error bound for strongly convex problems,where N is the iteration number.Symmetric ADMM can improve the algorithmic performance compared to classical ADMM,numerical experiments for statistical machine learning show that such an improvement is also present in the stochastic setting.展开更多
基金Sponsored by Jiangsu Planned Project for Postdoctoral (0901014B)
文摘The fire distribution can be divided into weapon assignment and firing time scheduling. The criterion of weapon allocation is that a target with greater threat has higher priority. And the criterion of firing time scheduling is that a target can be damaged with the expected probability before a specific time. A fire distribution scheme and a program for the integrated missile-gun air defense system based on a criterion of earlier damage were presented. An example was taken to illustrate its effectiveness.
基金Supported by National Natural Science Foundation of China (61662036)。
文摘Alternating direction method of multipliers(ADMM)receives much attention in the recent years due to various demands from machine learning and big data related optimization.In 2013,Ouyang et al.extend the ADMM to the stochastic setting for solving some stochastic optimization problems,inspired by the structural risk minimization principle.In this paper,we consider a stochastic variant of symmetric ADMM,named symmetric stochastic linearized ADMM(SSL-ADMM).In particular,using the framework of variational inequality,we analyze the convergence properties of SSL-ADMM.Moreover,we show that,with high probability,SSL-ADMM has O((ln N)·N^(-1/2))constraint violation bound and objective error bound for convex problems,and has O((ln N)^(2)·N^(-1))constraint violation bound and objective error bound for strongly convex problems,where N is the iteration number.Symmetric ADMM can improve the algorithmic performance compared to classical ADMM,numerical experiments for statistical machine learning show that such an improvement is also present in the stochastic setting.
