60 citations · 72 across the 4 of their papers we have counts for
5 papers
Large-scale Urban Facility Location Selection with Knowledge-informed Reinforcement Learning
Hongyuan Su, Yu Zheng, Jingtao Ding +2
The facility location problem (FLP) is a classical combinatorial optimization challenge aimed at strategically laying out facilities to maximize their accessibility. In this paper,…
Road Planning for Slums via Deep Reinforcement Learning
Yu Zheng, Hongyuan Su, Jingtao Ding +2
Millions of slum dwellers suffer from poor accessibility to urban services due to inadequate road infrastructure within slums, and road planning for slums is critical to the sustai…
Knowledge-driven Site Selection via Urban Knowledge Graph
Yu Liu, Jingtao Ding, Yong Li
Site selection determines optimal locations for new stores, which is of crucial importance to business success. Especially, the wide application of artificial intelligence with mul…
Simplify and Robustify Negative Sampling for Implicit Collaborative Filtering
Jingtao Ding, Yuhan Quan, Quanming Yao +2
Negative sampling approaches are prevalent in implicit collaborative filtering for obtaining negative labels from massive unlabeled data. As two major concerns in negative sampling…
Sampler Design for Bayesian Personalized Ranking by Leveraging View Data
Jingtao Ding, Guanghui Yu, Xiangnan He +2
Bayesian Personalized Ranking (BPR) is a representative pairwise learning method for optimizing recommendation models. It is widely known that the performance of BPR depends largel…