Leman Akoglu

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Christos FaloutsosCMUVerified email at cs.cmu.edu
Hanghang TongUniversity of Illinois at Urbana-ChampaignVerified email at illinois.edu
Lingxiao ZhaoCarnegie Mellon UniversityVerified email at andrew.cmu.edu
Danai KoutraUniversity of Michigan, Ann ArborVerified email at umich.edu
Tina Eliassi-RadProfessor & President Joseph E. Aoun Chair, Northeastern UniversityVerified email at eliassi.org
Shebuti RayanaAssistant Professor, SUNY at Old WestburyVerified email at cs.stonybrook.edu
Bart BaesensFull professor, KU LeuvenVerified email at kuleuven.be
Neil ShahResearch Scientist at SnapVerified email at snap.com
Yue ZhaoAssistant Professor of Computer Science, University of Southern CaliforniaVerified email at usc.edu
Duen Horng ChauAssociate Professor, Georgia Institute of TechnologyVerified email at gatech.edu
Brian GallagherComputer ScientistVerified email at briangallagher.net
Jilles VreekenCISPA Helmholtz Center for Information SecurityVerified email at cispa.de
Bryan PerozziGoogle ResearchVerified email at google.com
Bryan HooiNational University of SingaporeVerified email at comp.nus.edu.sg
Alex BeutelOpenAIVerified email at openai.com
U KangProfessor of Computer Science and Engineering, Seoul National UniversityVerified email at snu.ac.kr
Sugato BasuDistinguished Scientist at GoogleVerified email at google.com
Emaad ManzoorAssistant Professor of Marketing, Cornell UniversityVerified email at cornell.edu
Hau ChanAssistant Professor, University of Nebraska-LincolnVerified email at unl.edu
Pedro O.S Vaz-de-MeloProfessor de Ciência da Computação, Universidade Federal de Minas GeraisVerified email at dcc.ufmg.br

Leman Akoglu

Associate Professor, Carnegie Mellon University

Verified email at andrew.cmu.edu - Homepage

AI/ML Unsupervised Learning Anomaly/Fraud/Event Mining Graph Learning Neural Networks


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Graph based anomaly detection and description: a survey L Akoglu, H Tong, D Koutra Data mining and knowledge discovery 29, 626-688, 2015	1494	2015
Oddball: Spotting anomalies in weighted graphs L Akoglu, M McGlohon, C Faloutsos Advances in Knowledge Discovery and Data Mining: 14th Pacific-Asia …, 2010	717	2010
Collective opinion spam detection: Bridging review networks and metadata S Rayana, L Akoglu Proceedings of the 21th acm sigkdd international conference on knowledge …, 2015	562	2015
Opinion fraud detection in online reviews by network effects L Akoglu, R Chandy, C Faloutsos Proceedings of the International AAAI Conference on Web and Social Media 7 …, 2013	532	2013
Beyond homophily in graph neural networks: Current limitations and effective designs J Zhu, Y Yan, L Zhao, M Heimann, L Akoglu, D Koutra Advances in neural information processing systems 33, 7793-7804, 2020	525	2020
Rolx: structural role extraction & mining in large graphs K Henderson, B Gallagher, T Eliassi-Rad, H Tong, S Basu, L Akoglu, ... Proceedings of the 18th ACM SIGKDD international conference on Knowledge …, 2012	519	2012
A comprehensive survey on graph anomaly detection with deep learning X Ma, J Wu, S Xue, J Yang, C Zhou, QZ Sheng, H Xiong, L Akoglu IEEE Transactions on Knowledge and Data Engineering, 2021	486	2021
APATE: A novel approach for automated credit card transaction fraud detection using network-based extensions V Van Vlasselaer, C Bravo, O Caelen, T Eliassi-Rad, L Akoglu, M Snoeck, ... Decision Support Systems 75, 38-48, 2015	463	2015
Pairnorm: Tackling oversmoothing in gnns L Zhao, L Akoglu arXiv preprint arXiv:1909.12223, 2019	407	2019
It's who you know: graph mining using recursive structural features K Henderson, B Gallagher, L Li, L Akoglu, T Eliassi-Rad, H Tong, ... Proceedings of the 17th ACM SIGKDD international conference on Knowledge …, 2011	269	2011
Focused clustering and outlier detection in large attributed graphs B Perozzi, L Akoglu, P Iglesias Sánchez, E Müller Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014	267	2014
Fast memory-efficient anomaly detection in streaming heterogeneous graphs E Manzoor, SM Milajerdi, L Akoglu Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge …, 2016	202	2016
Discovering opinion spammer groups by network footprints J Ye, L Akoglu Machine Learning and Knowledge Discovery in Databases: European Conference …, 2015	182	2015
Event detection in time series of mobile communication graphs L Akoglu, C Faloutsos Army science conference 1, 141, 2010	182	2010
Gotcha! network-based fraud detection for social security fraud V Van Vlasselaer, T Eliassi-Rad, L Akoglu, M Snoeck, B Baesens Management Science 63 (9), 3090-3110, 2017	172	2017
Pics: Parameter-free identification of cohesive subgroups in large attributed graphs L Akoglu, H Tong, B Meeder, C Faloutsos Proceedings of the 2012 SIAM international conference on data mining, 439-450, 2012	172	2012
Weighted graphs and disconnected components: patterns and a generator M McGlohon, L Akoglu, C Faloutsos Proceedings of the 14th ACM SIGKDD international conference on Knowledge …, 2008	162	2008
Less is more: Building selective anomaly ensembles S Rayana, L Akoglu Acm transactions on knowledge discovery from data (tkdd) 10 (4), 1-33, 2016	152	2016
Fast and reliable anomaly detection in categorical data L Akoglu, H Tong, J Vreeken, C Faloutsos Proceedings of the 21st ACM international conference on Information and …, 2012	149	2012
Scalable anomaly ranking of attributed neighborhoods B Perozzi, L Akoglu Proceedings of the 2016 SIAM International Conference on Data Mining, 207-215, 2016	144	2016

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