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This survey gives a selective review of recent development of machine learning (ML) for combinatorial optimization (CO), especially for graph matching. The synergy of these two well-developed areas (ML and CO) can potentially give transformative change to artificial intelligence, whose foundation relates to these two building blocks. For its representativeness and wide-applicability, this paper is more focused on the problem of weighted graph matching, especially from the learning perspective.doi:10.24963/ijcai.2020/683 dblp:conf/ijcai/MathiasKMB20 fatcat:wzcx476gmvbdtoiqrt3owpzcea