25 citations · 36 across the 4 of their papers we have counts for
4 papers
Unlocking the Hidden Treasures: Enhancing Recommendations with Unlabeled Data
Yuhan Zhao, Rui Chen, Qilong Han +2
Collaborative filtering (CF) stands as a cornerstone in recommender systems, yet effectively leveraging the massive unlabeled data presents a significant challenge. Current researc…
From Pairwise to Ranking: Climbing the Ladder to Ideal Collaborative Filtering with Pseudo-Ranking
Yuhan Zhao, Rui Chen, Li Chen +3
Intuitively, an ideal collaborative filtering (CF) model should learn from users' full rankings over all items to make optimal top-K recommendations. Due to the absence of such ful…
SSDRec: Self-Augmented Sequence Denoising for Sequential Recommendation
Chi Zhang, Qilong Han, Rui Chen +3
Traditional sequential recommendation methods assume that users' sequence data is clean enough to learn accurate sequence representations to reflect user preferences. In practice,…
Augmented Negative Sampling for Collaborative Filtering
Yuhan Zhao, Rui Chen, Riwei Lai +3
Negative sampling is essential for implicit-feedback-based collaborative filtering, which is used to constitute negative signals from massive unlabeled data to guide supervised lea…