4 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.LG2026
FairGC: Fairness-aware Graph Condensation
Yihan Gao, Chenxi Huang, Wen Shi +5
Graph condensation (GC) has become a vital strategy for scaling Graph Neural Networks by compressing massive datasets into small, synthetic node sets. While current GC methods effe…
cs.IR2024
Multi-Objective Recommendation via Multivariate Policy Learning
Olivier Jeunen, Jatin Mandav, Ivan Potapov +4
Real-world recommender systems often need to balance multiple objectives when deciding which recommendations to present to users. These include behavioural signals (e.g. clicks, sh…
cs.IR2023★ 4 cited
On Gradient Boosted Decision Trees and Neural Rankers: A Case-Study on Short-Video Recommendations at ShareChat
Olivier Jeunen, Hitesh Sagtani, Himanshu Doi +7
Practitioners who wish to build real-world applications that rely on ranking models, need to decide which modelling paradigm to follow. This is not an easy choice to make, as the r…