Yuhang Zhou

Maximizing Cumulative User Engagement in Sequential Recommendation

2020

To maximize cumulative user engagement (e.g. cumulative clicks) in sequential recommendation, it is often needed to tradeoff two potentially conflicting objectives, that is, pursuing higher immediate user engagement (e.g., click-through rate) and encouraging user browsing …

Balanced Destruction-Reconstruction Dynamics for Memory-replay Class Incremental Learning

2023 · arXiv (Cornell University)

Class incremental learning (CIL) aims to incrementally update a trained model with the new classes of samples (plasticity) while retaining previously learned ability (stability). To address the most challenging issue in this goal, i.e., catastrophic …

Mosaic of Modalities: A Comprehensive Benchmark for Multimodal Graph Learning

2025

Graph machine learning has made significant strides in recent years, yet the integration of visual information with graph structure and its potential for improving performance in downstream tasks remains an underexplored area. To address this …