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Bridging the Gap between Spatial and Spectral Domains: A Theoretical Framework for Graph Neural Networks


Jul 21, 2021
Zhiqian Chen, Fanglan Chen, Lei Zhang, Taoran Ji, Kaiqun Fu, Liang Zhao, Feng Chen, Lingfei Wu, Charu Aggarwal, Chang-Tien Lu


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NRGNN: Learning a Label Noise-Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs


Jun 08, 2021
Enyan Dai, Charu Aggarwal, Suhang Wang


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Graph Feature Gating Networks


May 10, 2021
Wei Jin, Xiaorui Liu, Yao Ma, Tyler Derr, Charu Aggarwal, Jiliang Tang


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SetConv: A New Approach for Learning from Imbalanced Data


Apr 03, 2021
Yang Gao, Yi-Fan Li, Yu Lin, Charu Aggarwal, Latifur Khan

* Accepted by EMNLP 2020 (11 pages, 9 figures) 

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Meta-Learning with Graph Neural Networks: Methods and Applications


Feb 27, 2021
Debmalya Mandal, Sourav Medya, Brian Uzzi, Charu Aggarwal


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Information Prediction using Knowledge Graphs for Contextual Malware Threat Intelligence


Feb 18, 2021
Nidhi Rastogi, Sharmishtha Dutta, Ryan Christian, Mohammad Zaki, Alex Gittens, Charu Aggarwal

* 14 pages 

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Graph Convolutional Networks against Degree-Related Biases


Jun 28, 2020
Xianfeng Tang, Huaxiu Yao, Yiwei Sun, Yiqi Wang, Jiliang Tang, Charu Aggarwal, Prasenjit Mitra, Suhang Wang

* Preprint, under review 

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MALOnt: An Ontology for Malware Threat Intelligence


Jun 20, 2020
Nidhi Rastogi, Sharmishtha Dutta, Mohammed J. Zaki, Alex Gittens, Charu Aggarwal


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Non-IID Graph Neural Networks


May 22, 2020
Yiqi Wang, Yao Ma, Charu Aggarwal, Jiliang Tang


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Efficient Global String Kernel with Random Features: Beyond Counting Substructures


Nov 25, 2019
Lingfei Wu, Ian En-Hsu Yen, Siyu Huo, Liang Zhao, Kun Xu, Liang Ma, Shouling Ji, Charu Aggarwal

* KDD'19 Oral Paper, Data and Code link available in the paper 

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Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding


Nov 25, 2019
Lingfei Wu, Ian En-Hsu Yen, Zhen Zhang, Kun Xu, Liang Zhao, Xi Peng, Yinglong Xia, Charu Aggarwal

* KDD'19, Oral Paper, Data and Code link available in the paper 

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Joint Modeling of Local and Global Temporal Dynamics for Multivariate Time Series Forecasting with Missing Values


Nov 22, 2019
Xianfeng Tang, Huaxiu Yao, Yiwei Sun, Charu Aggarwal, Prasenjit Mitra, Suhang Wang

* Accepted by AAAI 2020 

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How can AI Automate End-to-End Data Science?


Oct 22, 2019
Charu Aggarwal, Djallel Bouneffouf, Horst Samulowitz, Beat Buesser, Thanh Hoang, Udayan Khurana, Sijia Liu, Tejaswini Pedapati, Parikshit Ram, Ambrish Rawat, Martin Wistuba, Alexander Gray


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Scalable Spectral Clustering Using Random Binning Features


Aug 11, 2018
Lingfei Wu, Pin-Yu Chen, Ian En-Hsu Yen, Fangli Xu, Yinglong Xia, Charu Aggarwal

* KDD'18, Oral Paper 

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REMIX: Automated Exploration for Interactive Outlier Detection


May 17, 2017
Yanjie Fu, Charu Aggarwal, Srinivasan Parthasarathy, Deepak S. Turaga, Hui Xiong

* To appear in KDD 2017 

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Joint Intermodal and Intramodal Label Transfers for Extremely Rare or Unseen Classes


Mar 22, 2017
Guo-Jun Qi, Wei Liu, Charu Aggarwal, Thomas Huang

* The paper has been accepted by IEEE Transactions on Pattern Analysis and Machine Intelligence. It will apear in a future issue 

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A Survey of Signed Network Mining in Social Media


Jun 20, 2016
Jiliang Tang, Yi Chang, Charu Aggarwal, Huan Liu

* 37 pages 

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Node Classification in Uncertain Graphs


May 22, 2014
Michele Dallachiesa, Charu Aggarwal, Themis Palpanas


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Learning from Collective Intelligence in Groups


Oct 03, 2012
Guo-Jun Qi, Charu Aggarwal, Pierre Moulin, Thomas Huang


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