61 citations · 302 across the 20 of their papers we have counts for
8 papers · 1 filter
To Predict or to Reject: Causal Effect Estimation with Uncertainty on Networked Data
Hechuan Wen, Tong Chen, Li Kheng Chai +3
Due to the imbalanced nature of networked observational data, the causal effect predictions for some individuals can severely violate the positivity/overlap assumption, rendering u…
Graph Contrastive Learning with Generative Adversarial Network
Cheng Wu, Chaokun Wang, Jingcao Xu +5
Graph Neural Networks (GNNs) have demonstrated promising results on exploiting node representations for many downstream tasks through supervised end-to-end training. To deal with t…
Graph Condensation for Inductive Node Representation Learning
Xinyi Gao, Tong Chen, Yilong Zang +4
Graph neural networks (GNNs) encounter significant computational challenges when handling large-scale graphs, which severely restricts their efficacy across diverse applications. T…
DeHIN: A Decentralized Framework for Embedding Large-scale Heterogeneous Information Networks
Mubashir Imran, Hongzhi Yin, Tong Chen +2
Modeling heterogeneity by extraction and exploitation of high-order information from heterogeneous information networks (HINs) has been attracting immense research attention in rec…
Unsupervised Time Series Outlier Detection with Diversity-Driven Convolutional Ensembles -- Extended Version
David Campos, Tung Kieu, Chenjuan Guo +4
With the sweeping digitalization of societal, medical, industrial, and scientific processes, sensing technologies are being deployed that produce increasing volumes of time series…
A Novel Approach to Lifelong Learning: The Plastic Support Structure
Georges Kanaan, Kai Wen Zheng, Lucas Fenaux
We propose a novel approach to lifelong learning, introducing a compact encapsulated support structure which endows a network with the capability to expand its capacity as needed t…
Equipping Experts/Bandits with Long-term Memory
Kai Zheng, Haipeng Luo, Ilias Diakonikolas +1
We propose the first reduction-based approach to obtaining long-term memory guarantees for online learning in the sense of Bousquet and Warmuth, 2002, by reducing the problem to ac…
RUM: network Representation learning throUgh Multi-level structural information preservation
Yanlei Yu, Zhiwu Lu, Jiajun Liu +3
We have witnessed the discovery of many techniques for network representation learning in recent years, ranging from encoding the context in random walks to embedding the lower ord…