44 citations · 168 across the 17 of their papers we have counts for
4 papers · 1 filter
Scalable Deep Graph Clustering with Random-walk based Self-supervised Learning
Xiang Li, Dong Li, Ruoming Jin +2
Web-based interactions can be frequently represented by an attributed graph, and node clustering in such graphs has received much attention lately. Multiple efforts have successful…
On Sampling Top-K Recommendation Evaluation
Dong Li, Ruoming Jin, Jing Gao +1
Recently, Rendle has warned that the use of sampling-based top- metrics might not suffice. This throws a number of recent studies on deep learning-based recommendation algorithm…
Towards a Better Understanding of Linear Models for Recommendation
Ruoming Jin, Dong Li, Jing Gao +3
Recently, linear regression models, such as EASE and SLIM, have shown to often produce rather competitive results against more sophisticated deep learning models. On the other side…
On Estimating Recommendation Evaluation Metrics under Sampling
Ruoming Jin, Dong Li, Benjamin Mudrak +2
Since the recent study (Krichene and Rendle 2020) done by Krichene and Rendle on the sampling-based top-k evaluation metric for recommendation, there has been a lot of debates on t…