26 citations · 38 across the 5 of their papers we have counts for
5 papers
EasyDGL: Encode, Train and Interpret for Continuous-time Dynamic Graph Learning
Chao Chen, Haoyu Geng, Nianzu Yang +2
Dynamic graphs arise in various real-world applications, and it is often welcomed to model the dynamics directly in continuous time domain for its flexibility. This paper aims to d…
Graph Signal Sampling for Inductive One-Bit Matrix Completion: a Closed-form Solution
Chao Chen, Haoyu Geng, Gang Zeng +4
Inductive one-bit matrix completion is motivated by modern applications such as recommender systems, where new users would appear at test stage with the ratings consisting of only…
Modeling Dynamic User Preference via Dictionary Learning for Sequential Recommendation
Chao Chen, Dongsheng Li, Junchi Yan +1
Capturing the dynamics in user preference is crucial to better predict user future behaviors because user preferences often drift over time. Many existing recommendation algorithms…
Learning Self-Modulating Attention in Continuous Time Space with Applications to Sequential Recommendation
Chao Chen, Haoyu Geng, Nianzu Yang +4
User interests are usually dynamic in the real world, which poses both theoretical and practical challenges for learning accurate preferences from rich behavior data. Among existin…
NeuSE: A Neural Snapshot Ensemble Method for Collaborative Filtering
Dongsheng Li, Haodong Liu, Chao Chen +3
In collaborative filtering (CF) algorithms, the optimal models are usually learned by globally minimizing the empirical risks averaged over all the observed data. However, the glob…