3 citations · 5 across the 4 of their papers we have counts for
4 papers
Network Design through Graph Neural Networks: Identifying Challenges and Improving Performance
Donald Loveland, Rajmonda Caceres
Graph Neural Network (GNN) research has produced strategies to modify a graph's edges using gradients from a trained GNN, with the goal of network design. However, the factors whic…
GRASP: Accelerating Shortest Path Attacks via Graph Attention
Zohair Shafi, Benjamin A. Miller, Ayan Chatterjee +2
Recent advances in machine learning (ML) have shown promise in aiding and accelerating classical combinatorial optimization algorithms. ML-based speed ups that aim to learn in an e…
Model Selection Framework for Graph-based data
Rajmonda S. Caceres, Leah Weiner, Matthew C. Schmidt +2
Graphs are powerful abstractions for capturing complex relationships in diverse application settings. An active area of research focuses on theoretical models that define the gener…
Locally Boosted Graph Aggregation for Community Detection
Jeremy Kun, Rajmonda Caceres, Kevin Carter
Learning the right graph representation from noisy, multi-source data has garnered significant interest in recent years. A central tenet of this problem is relational learning. Her…