Jundong Li

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Arizona State University ∙ University of Virginia ∙ Texas A&M University

Deep Structured Cross-Modal Anomaly Detection

Anomaly detection is a fundamental problem in data mining field with man...
08/11/2019 ∙ by Yuening Li, et al. ∙ 8 ∙ share

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Attributed Network Embedding for Learning in a Dynamic Environment

Network embedding leverages the node proximity manifested to learn a low...
06/06/2017 ∙ by Jundong Li, et al. ∙ 0 ∙ share

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Multi-Level Network Embedding with Boosted Low-Rank Matrix Approximation

As opposed to manual feature engineering which is tedious and difficult ...
08/26/2018 ∙ by Jundong Li, et al. ∙ 0 ∙ share

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A Survey of Learning Causality with Data: Problems and Methods

The era of big data provides researchers with convenient access to copio...
09/25/2018 ∙ by Ruocheng Guo, et al. ∙ 0 ∙ share

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Online Newton Step Algorithm with Estimated Gradient

Online learning with limited information feedback (bandit) tries to solv...
11/25/2018 ∙ by Binbin Liu, et al. ∙ 0 ∙ share

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Learning Individual Treatment Effects from Networked Observational Data

With convenient access to observational data, learning individual causal...
06/08/2019 ∙ by Ruocheng Guo, et al. ∙ 0 ∙ share

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Explaining Vulnerabilities to Adversarial Machine Learning through Visual Analytics

Machine learning models are currently being deployed in a variety of rea...
07/17/2019 ∙ by Yuxin Ma, et al. ∙ 0 ∙ share

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SpecAE: Spectral AutoEncoder for Anomaly Detection in Attributed Networks

Anomaly detection aims to distinguish observations that are rare and dif...
08/11/2019 ∙ by Yuening Li, et al. ∙ 0 ∙ share

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Graph Neural Networks with High-order Feature Interactions

Network representation learning, a fundamental research problem which ai...
08/19/2019 ∙ by Kaize Ding, et al. ∙ 0 ∙ share

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Generating Reliable Friends via Adversarial Training to Improve Social Recommendation

Most of the recent studies of social recommendation assume that people s...
09/08/2019 ∙ by Junliang Yu, et al. ∙ 0 ∙ share

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Scalable Attack on Graph Data by Injecting Vicious Nodes

Recent studies have shown that graph convolution networks (GCNs) are vul...
04/22/2020 ∙ by Jihong Wang, et al. ∙ 0 ∙ share

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Enhance Social Recommendation with Adversarial Graph Convolutional Networks

Recent reports from industry show that social recommender systems consis...
04/05/2020 ∙ by Junliang Yu, et al. ∙ 0 ∙ share

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Jundong Li

Featured Co-authors

Jiliang Tang

Xia Hu

Zi Huang

Huan Liu

Yi Chang

Xiao Huang

Mengnan Du

Hongzhi Yin

Ninghao Liu

Liang Wu

Yuening Li

Deep Structured Cross-Modal Anomaly Detection

Attributed Network Embedding for Learning in a Dynamic Environment

Multi-Level Network Embedding with Boosted Low-Rank Matrix Approximation

A Survey of Learning Causality with Data: Problems and Methods

Online Newton Step Algorithm with Estimated Gradient

Learning Individual Treatment Effects from Networked Observational Data

Explaining Vulnerabilities to Adversarial Machine Learning through Visual Analytics

SpecAE: Spectral AutoEncoder for Anomaly Detection in Attributed Networks

Graph Neural Networks with High-order Feature Interactions

Generating Reliable Friends via Adversarial Training to Improve Social Recommendation

Scalable Attack on Graph Data by Injecting Vicious Nodes

Enhance Social Recommendation with Adversarial Graph Convolutional Networks