2 citations · 3 across the 5 of their papers we have counts for
6 papers
Population Graph Cross-Network Node Classification for Autism Detection Across Sample Groups
Anna Stephens, Francisco Santos, Pang-Ning Tan +1
Graph neural networks (GNN) are a powerful tool for combining imaging and non-imaging medical information for node classification tasks. Cross-network node classification extends G…
Fairness Perception from a Network-Centric Perspective
Farzan Masrour, Pang-Ning Tan, Abdol-Hossein Esfahanian
Algorithmic fairness is a major concern in recent years as the influence of machine learning algorithms becomes more widespread. In this paper, we investigate the issue of algorith…
Some Preliminary Result About the Inset Edge and Average Distance of Trees
M. H. Khalifeh, A. -H. Esfahanian
An added edge to a graph is called an inset edge. Predicting k inset edges which minimize the average distance of a graph is known to be NP-Hard. However, when k = 1 the complexity…
Inset Edges Effect and Average Distance of Trees
M. H. Khalifeh, A. -H. Esfahanian
An added edge to a graph is called an inset edge. Predicting k inset edges which minimize the average distance of a graph is known to be NP-Hard. When k = 1 the complexity of the p…
Semi-supervised Collaborative Ranking with Push at Top
Iman Barjasteh, Rana Forsati, Abdol-Hossein Esfahanian +1
Existing collaborative ranking based recommender systems tend to perform best when there is enough observed ratings for each user and the observation is made completely at random.…
On Constructing Regular Distance-Preserving Graphs
Abdol-Hossein Esfahanian, Ronald Nussbaum, Dennis Ross +1
Let G be a simple, connected graph on n vertices. Let d_G(u,v) denote the distance between vertices u and v in G. A subgraph H of G is isometric if d_H(u,v)=d_G(u,v) for every u,v…