27 citations · 45 across the 5 of their papers we have counts for
5 papers
GMLP: Building Scalable and Flexible Graph Neural Networks with Feature-Message Passing
Wentao Zhang, Yu Shen, Zheyu Lin +6
In recent studies, neural message passing has proved to be an effective way to design graph neural networks (GNNs), which have achieved state-of-the-art performance in many graph-b…
Explore User Neighborhood for Real-time E-commerce Recommendation
Xu Xie, Fei Sun, Xiaoyong Yang +4
Recommender systems play a vital role in modern online services, such as Amazon and Taobao. Traditional personalized methods, which focus on user-item (UI) relations, have been wid…
Efficient Automatic CASH via Rising Bandits
Yang Li, Jiawei Jiang, Jinyang Gao +3
The Combined Algorithm Selection and Hyperparameter optimization (CASH) is one of the most fundamental problems in Automatic Machine Learning (AutoML). The existing Bayesian optimi…
Efficient and Scalable Structure Learning for Bayesian Networks: Algorithms and Applications
Rong Zhu, Andreas Pfadler, Ziniu Wu +6
Structure Learning for Bayesian network (BN) is an important problem with extensive research. It plays central roles in a wide variety of applications in Alibaba Group. However, ex…
Challenging the Long Tail Recommendation
Hongzhi Yin, Bin Cui, Jing Li +2
The success of "infinite-inventory" retailers such as Amazon.com and Netflix has been largely attributed to a "long tail" phenomenon. Although the majority of their inventory is no…