Jundong Li

According to our database1, Jundong Li authored at least 125 papers between 2014 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2022
Cross-Domain Graph Anomaly Detection.
IEEE Trans. Neural Networks Learn. Syst., 2022

A Deep Multi-View Framework for Anomaly Detection on Attributed Networks.
IEEE Trans. Knowl. Data Eng., 2022

LookCom: Learning Optimal Network for Community Detection.
IEEE Trans. Knowl. Data Eng., 2022

On Structural Explanation of Bias in Graph Neural Networks.
CoRR, 2022

Task-Adaptive Few-shot Node Classification.
CoRR, 2022

Benchmarking Node Outlier Detection on Graphs.
CoRR, 2022

TwiBot-22: Towards Graph-Based Twitter Bot Detection.
CoRR, 2022

Improving Fairness in Graph Neural Networks via Mitigating Sensitive Attribute Leakage.
CoRR, 2022

Towards Explanation for Unsupervised Graph-Level Representation Learning.
CoRR, 2022

FAITH: Few-Shot Graph Classification with Hierarchical Task Graphs.
CoRR, 2022

Empowering Next POI Recommendation with Multi-Relational Modeling.
CoRR, 2022

Fairness in Graph Mining: A Survey.
CoRR, 2022

KCD: Knowledge Walks and Textual Cues Enhanced Political Perspective Detection in News Media.
CoRR, 2022

Self-Supervised Learning for Recommender Systems: A Survey.
CoRR, 2022

Few-Shot Learning on Graphs: A Survey.
CoRR, 2022

Robust Unsupervised Graph Representation Learning via Mutual Information Maximization.
CoRR, 2022

Unbiased Graph Embedding with Biased Graph Observations.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Assessing the Causal Impact of COVID-19 Related Policies on Outbreak Dynamics: A Case Study in the US.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Geometric Graph Representation Learning via Maximizing Rate Reduction.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Learning Fair Node Representations with Graph Counterfactual Fairness.
Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

Graph Minimally-supervised Learning.
Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

Contrastive Attributed Network Anomaly Detection with Data Augmentation.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022

2021
Incremental one-class collaborative filtering with co-evolving side networks.
Knowl. Inf. Syst., 2021

Rumor2vec: A rumor detection framework with joint text and propagation structure representation learning.
Inf. Sci., 2021

Recommender systems based on generative adversarial networks: A problem-driven perspective.
Inf. Sci., 2021

Anomaly Detection Aided Budget Online Classification for Imbalanced Data Streams.
IEEE Intell. Syst., 2021

Weakly-supervised Graph Meta-learning for Few-shot Node Classification.
CoRR, 2021

Fairness-Aware Unsupervised Feature Selection.
CoRR, 2021

Graph Neural Networks with Adaptive Frequency Response Filter.
CoRR, 2021

Automated Generation of Interorganizational Disaster Response Networks through Information Extraction.
CoRR, 2021

Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation.
Proceedings of the WWW '21: The Web Conference 2021, 2021

Deconfounding with Networked Observational Data in a Dynamic Environment.
Proceedings of the WSDM '21, 2021

Toward User Engagement Optimization in 2D Presentation.
Proceedings of the WSDM '21, 2021

Data Efficient Learning on Graphs.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Anomaly and Novelty Detection, Explanation, and Accommodation (ANDEA).
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Unsupervised Graph Alignment with Wasserstein Distance Discriminator.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Individual Fairness for Graph Neural Networks: A Ranking based Approach.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Multi-Cause Effect Estimation with Disentangled Confounder Representation.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Double-Scale Self-Supervised Hypergraph Learning for Group Recommendation.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Fairness-Aware Unsupervised Feature Selection.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

REFORM: Error-Aware Few-Shot Knowledge Graph Completion.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

TwiBot-20: A Comprehensive Twitter Bot Detection Benchmark.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

SATAR: A Self-supervised Approach to Twitter Account Representation Learning and its Application in Bot Detection.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

AdaGNN: Graph Neural Networks with Adaptive Frequency Response Filter.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020
Explaining Vulnerabilities to Adversarial Machine Learning through Visual Analytics.
IEEE Trans. Vis. Comput. Graph., 2020

Nonlinear feature selection on attributed networks.
Neurocomputing, 2020

Using machine learning to predict ovarian cancer.
Int. J. Medical Informatics, 2020

Scalable attack on graph data by injecting vicious nodes.
Data Min. Knowl. Discov., 2020

A Survey of Learning Causality with Data: Problems and Methods.
ACM Comput. Surv., 2020

Line Graph Neural Networks for Link Prediction.
CoRR, 2020

Enhance Social Recommendation with Adversarial Graph Convolutional Networks.
CoRR, 2020

Learning Individual Causal Effects from Networked Observational Data.
Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 2020

Counterfactual Evaluation of Treatment Assignment Functions with Networked Observational Data.
Proceedings of the 2020 SIAM International Conference on Data Mining, 2020

IGNITE: A Minimax Game Toward Learning Individual Treatment Effects from Networked Observational Data.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Inductive Anomaly Detection on Attributed Networks.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Be More with Less: Hypergraph Attention Networks for Inductive Text Classification.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Unsupervised Hierarchical Feature Selection on Networked Data.
Proceedings of the Database Systems for Advanced Applications, 2020

Graph Few-shot Learning with Attribute Matching.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

Graph Prototypical Networks for Few-shot Learning on Attributed Networks.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

Scalable Social Tie Strength Measuring.
Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2020

Tracking Disaster Footprints with Social Streaming Data.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Learning with Attributed Networks: Algorithms and Applications.
PhD thesis, 2019

Towards privacy preserving social recommendation under personalized privacy settings.
World Wide Web, 2019

Graph Neural Networks with High-order Feature Interactions.
CoRR, 2019

Learning Individual Treatment Effects from Networked Observational Data.
CoRR, 2019

Interactive Anomaly Detection on Attributed Networks.
Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, 2019

XBully: Cyberbullying Detection within a Multi-Modal Context.
Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, 2019

Robust Factorization Machine: A Doubly Capped Norms Minimization.
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Deep Anomaly Detection on Attributed Networks.
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Adaptive Unsupervised Feature Selection on Attributed Networks.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Learning From Networks: Algorithms, Theory, and Applications.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Deep Structured Cross-Modal Anomaly Detection.
Proceedings of the International Joint Conference on Neural Networks, 2019

InterSpot: Interactive Spammer Detection in Social Media.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

PI-Bully: Personalized Cyberbullying Detection with Peer Influence.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Generating Reliable Friends via Adversarial Training to Improve Social Recommendation.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

Online Collaborative Filtering with Implicit Feedback.
Proceedings of the Database Systems for Advanced Applications, 2019

Anomaly Detection in Time-Evolving Attributed Networks.
Proceedings of the Database Systems for Advanced Applications, 2019

Heterogeneous Information Network Hashing for Fast Nearest Neighbor Search.
Proceedings of the Database Systems for Advanced Applications, 2019

SpecAE: Spectral AutoEncoder for Anomaly Detection in Attributed Networks.
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

Multi-level network embedding with boosted low-rank matrix approximation.
Proceedings of the ASONAM '19: International Conference on Advances in Social Networks Analysis and Mining, 2019

2018
A General Embedding Framework for Heterogeneous Information Learning in Large-Scale Networks.
ACM Trans. Knowl. Discov. Data, 2018

Exploiting Multilabel Information for Noise-Resilient Feature Selection.
ACM Trans. Intell. Syst. Technol., 2018

Toward online node classification on streaming networks.
Data Min. Knowl. Discov., 2018

Feature Selection: A Data Perspective.
ACM Comput. Surv., 2018

Online Newton Step Algorithm with Estimated Gradient.
CoRR, 2018

Multi-Level Network Embedding with Boosted Low-Rank Matrix Approximation.
CoRR, 2018

Understanding and Predicting Delay in Reciprocal Relations.
Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

Streaming Link Prediction on Dynamic Attributed Networks.
Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, 2018

Exploring Expert Cognition for Attributed Network Embedding.
Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, 2018

Multi-Layered Network Embedding.
Proceedings of the 2018 SIAM International Conference on Data Mining, 2018

Toward Relational Learning with Misinformation.
Proceedings of the 2018 SIAM International Conference on Data Mining, 2018

On Interpretation of Network Embedding via Taxonomy Induction.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

ANOMALOUS: A Joint Modeling Approach for Anomaly Detection on Attributed Networks.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

INITIATOR: Noise-contrastive Estimation for Marked Temporal Point Process.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Interactive Unknowns Recommendation in E-Learning Systems.
Proceedings of the IEEE International Conference on Data Mining, 2018

Adaptive Implicit Friends Identification over Heterogeneous Network for Social Recommendation.
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

Personalized Privacy-Preserving Social Recommendation.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Unsupervised Personalized Feature Selection.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Budget Online Learning Algorithm for Least Squares SVM.
IEEE Trans. Neural Networks Learn. Syst., 2017

Exploiting Expertise Rules for Statistical Data-Driven Modeling.
IEEE Trans. Ind. Electron., 2017

Exploiting statistically significant dependent rules for associative classification.
Intell. Data Anal., 2017

Challenges of Feature Selection for Big Data Analytics.
IEEE Intell. Syst., 2017

Understanding and Discovering Deliberate Self-harm Content in Social Media.
Proceedings of the 26th International Conference on World Wide Web, 2017

Label Informed Attributed Network Embedding.
Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, 2017

Gleaning Wisdom from the Past: Early Detection of Emerging Rumors in Social Media.
Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Toward Personalized Relational Learning.
Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Accelerated Attributed Network Embedding.
Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Sentiment Informed Cyberbullying Detection in Social Media.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Unsupervised Feature Selection in Signed Social Networks.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

Reconstruction-based Unsupervised Feature Selection: An Embedded Approach.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Radar: Residual Analysis for Anomaly Detection in Attributed Networks.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Attributed Network Embedding for Learning in a Dynamic Environment.
Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

Unsupervised Sentiment Analysis with Signed Social Networks.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
On discovering co-location patterns in datasets: a case study of pollutants and child cancers.
GeoInformatica, 2016

Robust Unsupervised Feature Selection on Networked Data.
Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

Multi-Label Informed Feature Selection.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Toward Time-Evolving Feature Selection on Dynamic Networks.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

FeatureMiner: A Tool for Interactive Feature Selection.
Proceedings of the 25th ACM International Conference on Information and Knowledge Management, 2016

2015
Associative Classification with Statistically Significant Positive and Negative Rules.
Proceedings of the 24th ACM International Conference on Information and Knowledge Management, 2015

Unsupervised Streaming Feature Selection in Social Media.
Proceedings of the 24th ACM International Conference on Information and Knowledge Management, 2015

2014
On Discovering Co-Location Patterns in Datasets: A Case Study of Pollutants and Child Cancers.
CoRR, 2014

Discovering Statistically Significant Co-location Rules in Datasets with Extended Spatial Objects.
Proceedings of the Data Warehousing and Knowledge Discovery, 2014

Active Learning Strategies for Semi-Supervised DBSCAN.
Proceedings of the Advances in Artificial Intelligence, 2014

Negative Association Rules.
Proceedings of the Frequent Pattern Mining, 2014


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