10 citations · 12 across the 4 of their papers we have counts for
4 papers · 1 filter
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,…
Adaptive Hardness Negative Sampling for Collaborative Filtering
Riwei Lai, Rui Chen, Qilong Han +2
Negative sampling is essential for implicit collaborative filtering to provide proper negative training signals so as to achieve desirable performance. We experimentally unveil a c…