Graph matching over two given graphs is a well-established method for re-identifying
obscured node labels within an anonymous graph by matching the corresponding nodes in …

The problem of graph matching involves finding a node correspondence between two
unlabeled graphs with known topologies, which has applications in various fields such as …

With the emergence of data marketplaces, the demand for methods to assess the value of
data has increased significantly. While numerous techniques have been proposed for this …

Node features bolster graph-based learning when exploited jointly with network structure.
However, a lack of nodal attributes is prevalent in graph data. We present a framework to …

Shuffled linear regression (SLR) seeks to estimate latent features through a linear
transformation, complicated by unknown permutations in the measurement dimensions. This …

Graph matching over two known graphs is a method for de-anonymizing obscured node
labels within an anonymous graph, finding the corresponding nodes in a second graph. In …