15 citations · 17 across the 3 of their papers we have counts for
3 papers
cs.IR2022★ 2 cited
Prototypical Contrastive Learning and Adaptive Interest Selection for Candidate Generation in Recommendations
Ningning Li, Qunwei Li, Xichen Ding +2
Deep Candidate Generation plays an important role in large-scale recommender systems. It takes user history behaviors as inputs and learns user and item latent embeddings for candi…
cs.AI2022
Device-Cloud Collaborative Recommendation via Meta Controller
Jiangchao Yao, Feng Wang, Xichen Ding +4
On-device machine learning enables the lightweight deployment of recommendation models in local clients, which reduces the burden of the cloud-based recommenders and simultaneously…
cs.IR2019★ 15 cited
Infer Implicit Contexts in Real-time Online-to-Offline Recommendation
Xichen Ding, Jie Tang, Tracy Liu +5
Understanding users' context is essential for successful recommendations, especially for Online-to-Offline (O2O) recommendation, such as Yelp, Groupon, and Koubei. Different from t…