584 citations · 3.1k across the 56 of their papers we have counts for
8 papers · 1 filter
Geometry Contrastive Learning on Heterogeneous Graphs
Shichao Zhu, Chuan Zhou, Anfeng Cheng +4
Self-supervised learning (especially contrastive learning) methods on heterogeneous graphs can effectively get rid of the dependence on supervisory data. Meanwhile, most existing r…
Data-Efficient Reinforcement Learning for Malaria Control
Lixin Zou, Long Xia, Linfang Hou +2
Sequential decision-making under cost-sensitive tasks is prohibitively daunting, especially for the problem that has a significant impact on people's daily lives, such as malaria c…
Enhanced Doubly Robust Learning for Debiasing Post-click Conversion Rate Estimation
Siyuan Guo, Lixin Zou, Yiding Liu +6
Post-click conversion, as a strong signal indicating the user preference, is salutary for building recommender systems. However, accurately estimating the post-click conversion rat…
CAST: A Correlation-based Adaptive Spectral Clustering Algorithm on Multi-scale Data
Xiang Li, Ben Kao, Caihua Shan +2
We study the problem of applying spectral clustering to cluster multi-scale data, which is data whose clusters are of various sizes and densities. Traditional spectral clustering t…
Robust Reinforcement Learning with Wasserstein Constraint
Linfang Hou, Liang Pang, Xin Hong +3
Robust Reinforcement Learning aims to find the optimal policy with some extent of robustness to environmental dynamics. Existing learning algorithms usually enable the robustness t…
GraphLIME: Local Interpretable Model Explanations for Graph Neural Networks
Qiang Huang, Makoto Yamada, Yuan Tian +3
Graph structured data has wide applicability in various domains such as physics, chemistry, biology, computer vision, and social networks, to name a few. Recently, graph neural net…