613 citations · 793 across the 10 of their papers we have counts for
12 papers
AutoField: Automating Feature Selection in Deep Recommender Systems
Yejing Wang, Xiangyu Zhao, Tong Xu +1
Feature quality has an impactful effect on recommendation performance. Thereby, feature selection is a critical process in developing deep learning-based recommender systems. Most…
Adversarial Neural Trip Recommendation
Linlang Jiang, Jingbo Zhou, Tong Xu +4
Trip recommender system, which targets at recommending a trip consisting of several ordered Points of Interest (POIs), has long been treated as an important application for many lo…
GeomGCL: Geometric Graph Contrastive Learning for Molecular Property Prediction
Shuangli Li, Jingbo Zhou, Tong Xu +2
Recently many efforts have been devoted to applying graph neural networks (GNNs) to molecular property prediction which is a fundamental task for computational drug and material di…
Intelligent Electric Vehicle Charging Recommendation Based on Multi-Agent Reinforcement Learning
Weijia Zhang, Hao Liu, Fan Wang +4
Electric Vehicle (EV) has become a preferable choice in the modern transportation system due to its environmental and energy sustainability. However, in many large cities, EV drive…
Drug Package Recommendation via Interaction-aware Graph Induction
Zhi Zheng, Chao Wang, Tong Xu +5
Recent years have witnessed the rapid accumulation of massive electronic medical records (EMRs), which highly support the intelligent medical services such as drug recommendation.…
Out-of-Town Recommendation with Travel Intention Modeling
Haoran Xin, Xinjiang Lu, Tong Xu +4
Out-of-town recommendation is designed for those users who leave their home-town areas and visit the areas they have never been to before. It is challenging to recommend Point-of-I…