Shelby Heinecke

Deconfounded Causal Collaborative Filtering

2021 · arXiv (Cornell University)

Recommender systems may be confounded by various types of confounding factors (also called confounders) that may lead to inaccurate recommendations and sacrificed recommendation performance. Current approaches to solving the problem usually design each specific model …

Personalized Multi-task Training for Recommender System

2024 · arXiv (Cornell University)

In the vast landscape of internet information, recommender systems (RecSys) have become essential for guiding users through a sea of choices aligned with their preferences. These systems have applications in diverse domains, such as news …