338 citations · 1.4k across the 59 of their papers we have counts for
4 papers · 1 filter
Optimizing Long-term Value for Auction-Based Recommender Systems via On-Policy Reinforcement Learning
Ruiyang Xu, Jalaj Bhandari, Dmytro Korenkevych +4
Auction-based recommender systems are prevalent in online advertising platforms, but they are typically optimized to allocate recommendation slots based on immediate expected retur…
Cascading Residual Graph Convolutional Network for Multi-Behavior Recommendation
Mingshi Yan, Zhiyong Cheng, Chen Gao +4
Multi-behavior recommendation exploits multiple types of user-item interactions to alleviate the data sparsity problem faced by the traditional models that often utilize only one t…
Disentangled Multimodal Representation Learning for Recommendation
Fan Liu, Huilin Chen, Zhiyong Cheng +3
Many multimodal recommender systems have been proposed to exploit the rich side information associated with users or items (e.g., user reviews and item images) for learning better…
Disentangled Graph Neural Networks for Session-based Recommendation
Ansong Li, Zhiyong Cheng, Fan Liu +3
Session-based recommendation (SBR) has drawn increasingly research attention in recent years, due to its great practical value by only exploiting the limited user behavior history…