46 citations · 98 across the 13 of their papers we have counts for
15 papers
Link Prediction without Graph Neural Networks
Zexi Huang, Mert Kosan, Arlei Silva +1
Link prediction, which consists of predicting edges based on graph features, is a fundamental task in many graph applications. As for several related problems, Graph Neural Network…
Robust Ante-hoc Graph Explainer using Bilevel Optimization
Kha-Dinh Luong, Mert Kosan, Arlei Lopes Da Silva +1
Explaining the decisions made by machine learning models for high-stakes applications is critical for increasing transparency and guiding improvements to these decisions. This is p…
A Broader Picture of Random-walk Based Graph Embedding
Zexi Huang, Arlei Silva, Ambuj Singh
Graph embedding based on random-walks supports effective solutions for many graph-related downstream tasks. However, the abundance of embedding literature has made it increasingly…
Event Detection on Dynamic Graphs
Mert Kosan, Arlei Silva, Sourav Medya +2
Event detection is a critical task for timely decision-making in graph analytics applications. Despite the recent progress towards deep learning on graphs, event detection on dynam…
POLE: Polarized Embedding for Signed Networks
Zexi Huang, Arlei Silva, Ambuj Singh
From the 2016 U.S. presidential election to the 2021 Capitol riots to the spread of misinformation related to COVID-19, many have blamed social media for today's deeply divided soc…
Feature-based Individual Fairness in k-Clustering
Debajyoti Kar, Mert Kosan, Debmalya Mandal +4
Ensuring fairness in machine learning algorithms is a challenging and essential task. We consider the problem of clustering a set of points while satisfying fairness constraints. W…