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ABSTRACT
In this paper, we consider a class of sparse inverse semidefinite quadratic programming problems, in which a nonconvex alternating direction method of multiplier is investigated. Under mild conditions, we establish convergence results of our algorithm and the corresponding non-ergodic iteration-complexity is also considered under the assumption that the potential function satisfies the famous Kurdyka–Łojasiewicz property. Numerical results show that our algorithm is suitable to solve the given sparse inverse semidefinite quadratic programming problems.
Disclosure statement
No potential conflict of interest was reported by the authors.
Additional information
Funding
The first author is supported by the National Natural Science Foundation of China [grant number 11601389] and the Doctoral Foundation of Tianjin Normal University [grant number 52XB1513]. The second author is supported by the National Natural Science Foundation of China [grant numbers 11626053 and 11701063], China Postdoctoral Science Foundation [grant number 2016M601296] and the Fundamental Research Funds for the Central Universities [grant numbers 3132016108 and 3132017052] and the Scientific Research Foundation Funds of DLMU [grant number 02501102]. The third author is supported by the National Natural Science Foundation of China [grant number 11401210].