Collaborative Research: BLoG: A Bi-Level Optimization Framework for Learning Over Graphs — NSF Award to Cornell University (NY, $2
Graphs, representing complex sensing and other societal systems like disease networks, social networks, and communication networks, are essential in understanding interactions within these systems. By accurately modeling relationships and structures within data via graphs, today machine learning over graphs (LoGs) play
| Award title | Collaborative Research: BLoG: A Bi-Level Optimization Framework for Learning Over Graphs |
|---|---|
| Award ID | 2532653 |
| Awardee | Cornell University |
| City | ITHACA |
| State | NY |
| Amount obligated | $250,002 |
| Principal investigator | Tianyi Chen |
| Program | CSCS: Circuits and Systems for |
| Start date | 08/01/2025 |
| Abstract | Graphs, representing complex sensing and other societal systems like disease networks, social networks, and communication networks, are essential in understanding interactions within these systems. By accurately modeling relationships and structures within data via graphs, today machine learning over graphs (LoGs) plays a vital role in various applications. However, LoG introduces additional hyperparameters such as graph topologies and nodal embeddings into the already complicated neural network |
| Source | NSF Awards |
$799/mo
Try NSFGrants →