3 papers
stat.ML2026
Subspace Projection Methods for Fast Spectral Embeddings of Evolving Graphs
Mohammad Eini, Abdullah Karaaslanli, Vassilis Kalantzis +1
Several graph data mining, signal processing, and machine learning downstream tasks rely on information related to the eigenvectors of the associated adjacency or Laplacian matrix.…
stat.ML2025
Signed Graph Learning: Algorithms and Theory
Abdullah Karaaslanli, Bisakh Banerjee, Tapabrata Maiti +1
Real-world data is often represented through the relationships between data samples, forming a graph structure. In many applications, it is necessary to learn this graph structure…
cs.SI2024
Learning Graph Filters for Structure-Function Coupling based Hub Node Identification
Meiby Ortiz-Bouza, Duc Vu, Abdullah Karaaslanli +1
Over the past two decades, tools from network science have been leveraged to characterize the organization of both structural and functional networks of the brain. One such measure…