Charu C. Aggarwal

ORCID

Publication Activity (10 Years)

Years Active: 1995-2024
Publications (10 Years): 170

Top Venues

Publications

Jin Li, Shoujin Wang, Qi Zhang, Longbing Cao, Fang Chen, Xiuzhen Zhang, Dietmar Jannach, Charu C. Aggarwal
Causal Learning for Trustworthy Recommender Systems: A Survey. CoRR (2024)
Harry Shomer, Yao Ma, Juanhui Li, Bo Wu, Charu C. Aggarwal, Jiliang Tang
Distance-Based Propagation for Efficient Knowledge Graph Reasoning. CoRR (2023)
Haoyu Han, Xiaorui Liu, Feng Shi, MohamadAli Torkamani, Charu C. Aggarwal, Jiliang Tang
Towards Label Position Bias in Graph Neural Networks. CoRR (2023)
Zhichao Hou, Xitong Zhang, Wei Wang, Charu C. Aggarwal, Xiaorui Liu
Can Directed Graph Neural Networks be Adversarially Robust? CoRR (2023)
Harry Shomer, Yao Ma, Juanhui Li, Bo Wu, Charu C. Aggarwal, Jiliang Tang
Distance-Based Propagation for Efficient Knowledge Graph Reasoning. EMNLP (2023)
Zitai Qiu, Jia Wu, Jian Yang, Xing Su, Charu C. Aggarwal
Heterogeneous Social Event Detection via Hyperbolic Graph Representations. CoRR (2023)
Haoyu Han, Xiaorui Liu, Feng Shi, MohamadAli Torkamani, Charu C. Aggarwal, Jiliang Tang
Towards Label Position Bias in Graph Neural Networks. NeurIPS (2023)
Jing Ren, Feng Xia, Ivan Lee, Azadeh Noori Hoshyar, Charu C. Aggarwal
Graph Learning for Anomaly Analytics: Algorithms, Applications, and Challenges. ACM Trans. Intell. Syst. Technol. 14 (2) (2023)
Jianxin Li, Lifang He, Hao Peng, Peng Cui, Charu C. Aggarwal, Philip S. Yu
Guest Editorial Introduction to the Special Issue on Anomaly Detection in Emerging Data-Driven Applications: Theory, Algorithms, and Applications. IEEE Trans. Knowl. Data Eng. 35 (12) (2023)
Pengfei He, Han Xu, Jie Ren, Yingqian Cui, Hui Liu, Charu C. Aggarwal, Jiliang Tang
Sharpness-Aware Data Poisoning Attack. CoRR (2023)
Wenqi Fan, Han Xu, Wei Jin, Xiaorui Liu, Xianfeng Tang, Suhang Wang, Qing Li, Jiliang Tang, Jianping Wang, Charu C. Aggarwal
Jointly Attacking Graph Neural Network and its Explanations. ICDE (2023)
Zhenyu Yang, Ge Zhang, Jia Wu, Jian Yang, Quan Z. Sheng, Shan Xue, Chuan Zhou, Charu C. Aggarwal, Hao Peng, Wenbin Hu, Edwin Hancock, Pietro Li'o
A Comprehensive Survey of Graph-level Learning. CoRR (2023)
Jaykumar Kakkad, Jaspal Jannu, Kartik Sharma, Charu C. Aggarwal, Sourav Medya
A Survey on Explainability of Graph Neural Networks. CoRR (2023)
Yuying Zhao, Yu Wang, Yunchao Liu, Xueqi Cheng, Charu C. Aggarwal, Tyler Derr
Fairness and Diversity in Recommender Systems: A Survey. CoRR (2023)
Wei Jin, Xiaorui Liu, Yao Ma, Charu C. Aggarwal, Jiliang Tang
Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective. CoRR (2022)
Wei Jin, Xiaorui Liu, Yao Ma, Charu C. Aggarwal, Jiliang Tang
Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective. KDD (2022)
Fanzhen Liu, Xiaoxiao Ma, Jia Wu, Jian Yang, Shan Xue, Amin Beheshti, Chuan Zhou, Hao Peng, Quan Z. Sheng, Charu C. Aggarwal
DAGAD: Data Augmentation for Graph Anomaly Detection. CoRR (2022)
Djallel Bouneffouf, Charu C. Aggarwal
Survey on Applications of Neurosymbolic Artificial Intelligence. CoRR (2022)
Fanzhen Liu, Xiaoxiao Ma, Jia Wu, Jian Yang, Shan Xue, Amin Beheshti, Chuan Zhou, Hao Peng, Quan Z. Sheng, Charu C. Aggarwal
DAGAD: Data Augmentation for Graph Anomaly Detection. ICDM (2022)
Charu C. Aggarwal
An Interview with Dr. Charu Aggarwal, Winner of ACM SIGKDD 2022 Service Award. SIGKDD Explor. 24 (2) (2022)
Zhiqiang Hu, Roy Ka-Wei Lee, Charu C. Aggarwal, Aston Zhang
Text Style Transfer: A Review and Experimental Evaluation. SIGKDD Explor. 24 (1) (2022)
Jing Ren, Feng Xia, Azadeh Noori Hoshyar, Charu C. Aggarwal
Graph Learning for Anomaly Analytics: Algorithms, Applications, and Challenges. CoRR (2022)
Zahra Zamanzadeh Darban, Geoffrey I. Webb, Shirui Pan, Charu C. Aggarwal, Mahsa Salehi
Deep Learning for Time Series Anomaly Detection: A Survey. CoRR (2022)
Shijie Zhou, Zhimeng Guo, Charu C. Aggarwal, Xiang Zhang, Suhang Wang
Link Prediction on Heterophilic Graphs via Disentangled Representation Learning. CoRR (2022)
Charu C. Aggarwal
Communication from the Editor-in-Chief: State of the ACM Transactions on Knowledge Discovery from Data. ACM Trans. Knowl. Discov. Data 16 (2) (2022)
Ge Zhang, Zhenyu Yang, Jia Wu, Jian Yang, Shan Xue, Hao Peng, Jianlin Su, Chuan Zhou, Quan Z. Sheng, Leman Akoglu, Charu C. Aggarwal
Dual-discriminative Graph Neural Network for Imbalanced Graph-level Anomaly Detection. NeurIPS (2022)
Nidhi Rastogi, Sharmishtha Dutta, Alex Gittens, Mohammed J. Zaki, Charu C. Aggarwal
TINKER: A framework for Open source Cyberthreat Intelligence. TrustCom (2022)
Nurendra Choudhary, Charu C. Aggarwal, Karthik Subbian, Chandan K. Reddy
Self-supervised Short-text Modeling through Auxiliary Context Generation. ACM Trans. Intell. Syst. Technol. 13 (3) (2022)
Yuxiang Ren, Charu C. Aggarwal, Jiawei Zhang
ActiveIter: Meta Diagram Based Active Learning in Social Networks Alignment. IEEE Trans. Knowl. Data Eng. 33 (5) (2021)
Zhiqiang Hu, Roy Ka-Wei Lee, Charu C. Aggarwal
Syntax Matters! Syntax-Controlled in Text Style Transfer. CoRR (2021)
Enyan Dai, Charu C. Aggarwal, Suhang Wang
NRGNN: Learning a Label Noise-Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs. CoRR (2021)
Zhiqian Chen, Fanglan Chen, Lei Zhang, Taoran Ji, Kaiqun Fu, Liang Zhao, Feng Chen, Lingfei Wu, Charu C. Aggarwal, Chang-Tien Lu
Bridging the Gap between Spatial and Spectral Domains: A Theoretical Framework for Graph Neural Networks. CoRR (2021)
Nidhi Rastogi, Sharmishtha Dutta, Christian Ryan, Mohammad Zaki, Alex Gittens, Charu C. Aggarwal
Information Prediction using Knowledge Graphs for Contextual Malware Threat Intelligence. CoRR (2021)
Wei Jin, Xiaorui Liu, Yao Ma, Tyler Derr, Charu C. Aggarwal, Jiliang Tang
Graph Feature Gating Networks. CIKM (2021)
Charu C. Aggarwal, Yao Li, Philip S. Yu
Signature-Based Anomaly Detection in Networks. SDM (2021)
Guansong Pang, Charu C. Aggarwal
Toward Explainable Deep Anomaly Detection. KDD (2021)
Wei Jin, Xiaorui Liu, Yao Ma, Tyler Derr, Charu C. Aggarwal, Jiliang Tang
Graph Feature Gating Networks. CoRR (2021)
Wenqi Fan, Wei Jin, Xiaorui Liu, Han Xu, Xianfeng Tang, Suhang Wang, Qing Li, Jiliang Tang, Jianping Wang, Charu C. Aggarwal
Jointly Attacking Graph Neural Network and its Explanations. CoRR (2021)
Yang Gao, Yi-Fan Li, Yu Lin, Charu C. Aggarwal, Latifur Khan
SetConv: A New Approach for Learning from Imbalanced Data. CoRR (2021)
Zhiqiang Hu, Roy Ka-Wei Lee, Charu C. Aggarwal
Syntax Matters! Syntax-Controlled in Text Style Transfer. RANLP (2021)
Xianfeng Tang, Huaxiu Yao, Yiwei Sun, Charu C. Aggarwal, Prasenjit Mitra, Suhang Wang
Joint Modeling of Local and Global Temporal Dynamics for Multivariate Time Series Forecasting with Missing Values. AAAI (2020)
Djallel Bouneffouf, Charu C. Aggarwal, Thanh Hoang, Udayan Khurana, Horst Samulowitz, Beat Buesser, Sijia Liu, Tejaswini Pedapati, Parikshit Ram, Ambrish Rawat, Martin Wistuba, Alexander G. Gray
Survey on Automated End-to-End Data Science? IJCNN (2020)
Yang Gao, Yi-Fan Li, Yu Lin, Charu C. Aggarwal, Latifur Khan
SetConv: A New Approach for Learning from Imbalanced Data. EMNLP (1) (2020)
Juan-Hui Li, Yao Ma, Yiqi Wang, Charu C. Aggarwal, Chang-Dong Wang, Jiliang Tang
Graph Pooling with Representativeness. ICDM (2020)
Nidhi Rastogi, Sharmishtha Dutta, Mohammed J. Zaki, Alex Gittens, Charu C. Aggarwal
MALOnt: An Ontology for Malware Threat Intelligence. CoRR (2020)
Tyler Derr, Yao Ma, Wenqi Fan, Xiaorui Liu, Charu C. Aggarwal, Jiliang Tang
Epidemic Graph Convolutional Network. WSDM (2020)
Zhiqiang Hu, Roy Ka-Wei Lee, Charu C. Aggarwal
Text Style Transfer: A Review and Experiment Evaluation. CoRR (2020)
Charu C. Aggarwal, Yao Li, Philip S. Yu
On Supervised Change Detection in Graph Streams. SDM (2020)
Djallel Bouneffouf, Irina Rish, Charu C. Aggarwal
Survey on Applications of Multi-Armed and Contextual Bandits. CEC (2020)
Xianfeng Tang, Huaxiu Yao, Yiwei Sun, Yiqi Wang, Jiliang Tang, Charu C. Aggarwal, Prasenjit Mitra, Suhang Wang
Investigating and Mitigating Degree-Related Biases in Graph Convoltuional Networks. CIKM (2020)
Xianfeng Tang, Huaxiu Yao, Yiwei Sun, Yiqi Wang, Jiliang Tang, Charu C. Aggarwal, Prasenjit Mitra, Suhang Wang
Graph Convolutional Networks against Degree-Related Biases. CoRR (2020)
Yiqi Wang, Yao Ma, Charu C. Aggarwal, Jiliang Tang
Non-IID Graph Neural Networks. CoRR (2020)
Lingfei Wu, Ian En-Hsu Yen, Siyu Huo, Liang Zhao, Kun Xu, Liang Ma, Shouling Ji, Charu C. Aggarwal
Efficient Global String Kernel with Random Features: Beyond Counting Substructures. CoRR (2019)
Liang Duan, Charu C. Aggarwal, Shuai Ma, Saket Sathe
Improving Spectral Clustering with Deep Embedding and Cluster Estimation. ICDM (2019)
Yuxiang Ren, Charu C. Aggarwal, Jiawei Zhang
Meta Diagram based Active Social Networks Alignment. CoRR (2019)
Lingfei Wu, Ian En-Hsu Yen, Zhen Zhang, Kun Xu, Liang Zhao, Xi Peng, Yinglong Xia, Charu C. Aggarwal
Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding. CoRR (2019)
Suhang Wang, Charu C. Aggarwal, Huan Liu
Beyond word2vec: Distance-graph Tensor Factorization for Word and Document Embeddings. CIKM (2019)
Yao Ma, Suhang Wang, Charu C. Aggarwal, Jiliang Tang
Graph Convolutional Networks with EigenPooling. CoRR (2019)
Bowen Dong, Charu C. Aggarwal, Philip S. Yu
The Link Regression Problem in Graph Streams. IEEE BigData (2019)
Karthik S. Gurumoorthy, Amit Dhurandhar, Guillermo A. Cecchi, Charu C. Aggarwal
Efficient Data Representation by Selecting Prototypes with Importance Weights. ICDM (2019)
Lingfei Wu, Ian En-Hsu Yen, Zhen Zhang, Kun Xu, Liang Zhao, Xi Peng, Yinglong Xia, Charu C. Aggarwal
Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding. KDD (2019)
Lingfei Wu, Ian En-Hsu Yen, Siyu Huo, Liang Zhao, Kun Xu, Liang Ma, Shouling Ji, Charu C. Aggarwal
Efficient Global String Kernel with Random Features: Beyond Counting Substructures. KDD (2019)
Wenchao Yu, Wei Cheng, Charu C. Aggarwal, Bo Zong, Haifeng Chen, Wei Wang
Self-Attentive Attributed Network Embedding Through Adversarial Learning. ICDM (2019)
Charu C. Aggarwal, Djallel Bouneffouf, Horst Samulowitz, Beat Buesser, Thanh Hoang, Udayan Khurana, Sijia Liu, Tejaswini Pedapati, Parikshit Ram, Ambrish Rawat, Martin Wistuba, Alexander G. Gray
How can AI Automate End-to-End Data Science? CoRR (2019)
Michele Dallachiesa, Charu C. Aggarwal, Themis Palpanas
Improving Classification Quality in Uncertain Graphs. ACM J. Data Inf. Qual. 11 (1) (2019)
Xianfeng Tang, Huaxiu Yao, Yiwei Sun, Charu C. Aggarwal, Prasenjit Mitra, Suhang Wang
Joint Modeling of Local and Global Temporal Dynamics for Multivariate Time Series Forecasting with Missing Values. CoRR (2019)
Yuxiang Ren, Charu C. Aggarwal, Jiawei Zhang
Meta Diagram Based Active Social Networks Alignment. ICDE (2019)
Yao Ma, Suhang Wang, Charu C. Aggarwal, Jiliang Tang
Graph Convolutional Networks with EigenPooling. KDD (2019)
Bowen Dong, Charu C. Aggarwal, Philip S. Yu
Transfer Learning for Network Classification. IJCNN (2019)
Kemilly Dearo Garcia, Elaine Ribeiro de Faria, Cláudio Rebelo de Sá, João Mendes-Moreira, Charu C. Aggarwal, André C. P. L. F. de Carvalho, Joost N. Kok
Ensemble Clustering for Novelty Detection in Data Streams. DS (2019)
Yao Ma, Suhang Wang, Charu C. Aggarwal, Dawei Yin, Jiliang Tang
Multi-dimensional Graph Convolutional Networks. SDM (2019)
Saket Sathe, Charu C. Aggarwal
Nearest Neighbor Classifiers Versus Random Forests and Support Vector Machines. ICDM (2019)
Lingfei Wu, Pin-Yu Chen, Ian En-Hsu Yen, Fangli Xu, Yinglong Xia, Charu C. Aggarwal
Scalable Spectral Clustering Using Random Binning Features. CoRR (2018)
Muchen Wu, Charu C. Aggarwal, Zhou Yu, Ananthram Swami, Prasant Mohapatra
Exploiting Knowledge Across Distinct Domains: Learning Event Details from Network Logs. MILCOM (2018)
Yao Ma, Suhang Wang, Charu C. Aggarwal, Dawei Yin, Jiliang Tang
Multi-dimensional Graph Convolutional Networks. CoRR (2018)
Saket Sathe, Charu C. Aggarwal
Subspace histograms for outlier detection in linear time. Knowl. Inf. Syst. 56 (3) (2018)
Wenchao Yu, Cheng Zheng, Wei Cheng, Charu C. Aggarwal, Dongjin Song, Bo Zong, Haifeng Chen, Wei Wang
Learning Deep Network Representations with Adversarially Regularized Autoencoders. KDD (2018)
Ana Paula Appel, Renato Luiz de Freitas Cunha, Charu C. Aggarwal, Marcela Megumi Terakado
Temporally Evolving Community Detection and Prediction in Content-Centric Networks. ECML/PKDD (2) (2018)
Suhang Wang, Charu C. Aggarwal, Huan Liu
Random-Forest-Inspired Neural Networks. ACM Trans. Intell. Syst. Technol. 9 (6) (2018)
Pengyang Wang, Jiawei Zhang, Guannan Liu, Yanjie Fu, Charu C. Aggarwal
Ensemble-Spotting: Ranking Urban Vibrancy via POI Embedding with Multi-view Spatial Graphs. SDM (2018)
Xindong Wu, Charu C. Aggarwal
Editorial: TKDD Special Issue on Interactive Data Exploration and Analytics. ACM Trans. Knowl. Discov. Data 12 (1) (2018)
Wenchao Yu, Charu C. Aggarwal, Wei Wang
Modeling Co-Evolution Across Multiple Networks. SDM (2018)
Swarup Chandra, Ahsanul Haque, Hemeng Tao, Jie Liu, Latifur Khan, Charu C. Aggarwal
Ensemble Direct Density Ratio Estimation for Multistream Classification. ICDE (2018)
Wenchao Yu, Wei Cheng, Charu C. Aggarwal, Kai Zhang, Haifeng Chen, Wei Wang
NetWalk: A Flexible Deep Embedding Approach for Anomaly Detection in Dynamic Networks. KDD (2018)
Pengyang Wang, Yanjie Fu, Jiawei Zhang, Pengfei Wang, Yu Zheng, Charu C. Aggarwal
You Are How You Drive: Peer and Temporal-Aware Representation Learning for Driving Behavior Analysis. KDD (2018)
Ana Paula Appel, Renato Luiz de Freitas Cunha, Charu C. Aggarwal, Marcela Megumi Terakado
Temporally Evolving Community Detection and Prediction in Content-Centric Networks. CoRR (2018)
Lingfei Wu, Pin-Yu Chen, Ian En-Hsu Yen, Fangli Xu, Yinglong Xia, Charu C. Aggarwal
Scalable Spectral Clustering Using Random Binning Features. KDD (2018)
Tyler Derr, Charu C. Aggarwal, Jiliang Tang
Signed Network Modeling Based on Structural Balance Theory. CIKM (2018)
Charu C. Aggarwal
Extracting Real-Time Insights from Graphs and Social Streams. SIGIR (2018)
Jinghui Chen, Saket Sathe, Charu C. Aggarwal, Deepak S. Turaga
Outlier Detection with Autoencoder Ensembles. SDM (2017)
Suhang Wang, Charu C. Aggarwal, Jiliang Tang, Huan Liu
Attributed Signed Network Embedding. CIKM (2017)
Weike Pan, Qiang Yang, Charu C. Aggarwal, Christoph Koch
Big Data. IEEE Intell. Syst. 32 (2) (2017)
Karthik Subbian, Charu C. Aggarwal
Mining Social Streams: Models and Applications. IEEE Data Eng. Bull. 40 (3) (2017)
Wenchao Yu, Charu C. Aggarwal, Wei Wang
Temporally Factorized Network Modeling for Evolutionary Network Analysis. WSDM (2017)
Yanjie Fu, Charu C. Aggarwal, Srinivasan Parthasarathy, Deepak S. Turaga, Hui Xiong
REMIX: Automated Exploration for Interactive Outlier Detection. KDD (2017)
Guo-Jun Qi, Wei Liu, Charu C. Aggarwal, Thomas S. Huang
Joint Intermodal and Intramodal Label Transfers for Extremely Rare or Unseen Classes. IEEE Trans. Pattern Anal. Mach. Intell. 39 (7) (2017)
Guo-Jun Qi, Wei Liu, Charu C. Aggarwal, Thomas S. Huang
Joint Intermodal and Intramodal Label Transfers for Extremely Rare or Unseen Classes. CoRR (2017)
Yanjie Fu, Charu C. Aggarwal, Srinivasan Parthasarathy, Deepak S. Turaga, Hui Xiong
REMIX: Automated Exploration for Interactive Outlier Detection. CoRR (2017)
Liheng Zhang, Charu C. Aggarwal, Guo-Jun Qi
Stock Price Prediction via Discovering Multi-Frequency Trading Patterns. KDD (2017)
Charu C. Aggarwal, Yao Li, Philip S. Yu, Yuchen Zhao
On Edge Classification in Networks with Structure and Content. ICDE (2017)

Charu C. Aggarwal.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Charu C. Aggarwal