27 citations · 27 across the 2 of their papers we have counts for
2 papers
cs.IR2023
Contrastive State Augmentations for Reinforcement Learning-Based Recommender Systems
Zhaochun Ren, Na Huang, Yidan Wang +7
Learning reinforcement learning (RL)-based recommenders from historical user-item interaction sequences is vital to generate high-reward recommendations and improve long-term cumul…
cs.IR2022★ 27 cited
Debiasing Learning for Membership Inference Attacks Against Recommender Systems
Zihan Wang, Na Huang, Fei Sun +5
Learned recommender systems may inadvertently leak information about their training data, leading to privacy violations. We investigate privacy threats faced by recommender systems…