2 papers
cs.SI2026
Fairness-Aware Network Embeddings: Methods, Applications, and Challenges
Ella Has, Harshith Kumar Yadav, Gaurav Dixit +2
Network embedding methods learn low-dimensional representations of graph-structured data to support downstream tasks such as node classification, link prediction, and influence max…
cs.LG2025
DQ4FairIM: Fairness-aware Influence Maximization using Deep Reinforcement Learning
Akrati Saxena, Harshith Kumar Yadav, Bart Rutten +1
The Influence Maximization (IM) problem aims to select a set of seed nodes within a given budget to maximize the spread of influence in a social network. However, real-world social…