Graph matching, which refers to a class of computational problems of finding an optimal
correspondence between the vertices of graphs to minimize (maximize) their node and edge …

Graph matching refers to finding node correspondence between graphs, such that the
corresponding node and edge's affinity can be maximized. In addition with its NP …

Metro passenger flow prediction is a strategically necessary demand in an intelligent
transportation system to alleviate traffic pressure, coordinate operation schedules, and plan …

The problem of graph matching under node and pair-wise constraints is fundamental in
areas as diverse as combinatorial optimization, machine learning or computer vision, where …

Graph matching involves combinatorial optimization based on edge-to-edge affinity matrix,
which can be generally formulated as Lawler's quadratic assignment problem (QAP). This …

Graph matching aims to establish node correspondence between two graphs, which has
been a fundamental problem for its NP-hard nature. One practical consideration is the …

This paper addresses the problem of matching common node correspondences among
multiple graphs referring to an identical or related structure. This multi-graph matching …

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 …

Hypergraph matching is a useful tool to find feature correspondence by considering higher-
order structural information. Recently, the employment of deep learning has made great …

Efficient numerical linear algebra is a core ingredient in many applications across almost all
scientific and industrial disciplines. With this survey we want to illustrate that numerical linear …