RTM: Laws and a Recursive Generator for Weighted Time-Evolving Graphs. - Leman Akoglu; Mary McGlohon; Christos Faloutsos (ICDM, 2008)

Weighted graphs and disconnected components: patterns and a generator. - Mary McGlohon; Leman Akoglu; Christos Faloutsos (KDD, 2008)

Large human communication networks: patterns and a utility-driven generator. - Nan Du; Christos Faloutsos; Bai Wang 001; Leman Akoglu (KDD, 2009)

RTG: a recursive realistic graph generator using random typing. - Leman Akoglu; Christos Faloutsos (Data Min. Knowl. Discov., 2009)

ValuePick: Towards a Value-Oriented Dual-Goal Recommender System. - Leman Akoglu; Christos Faloutsos (ICDM Workshops, 2010)

Patterns on the Connected Components of Terabyte-Scale Graphs. - U Kang; Mary McGlohon; Leman Akoglu; Christos Faloutsos (ICDM, 2010)

Metric forensics: a multi-level approach for mining volatile graphs. - Keith Henderson; Tina Eliassi-Rad; Christos Faloutsos; Leman Akoglu; Lei Li 005; Koji Maruhashi; B. Aditya Prakash; Hanghang Tong (KDD, 2010)

Structure, tie persistence and event detection in large phone and SMS networks. - Leman Akoglu; Bhavana Dalvi (MLG@KDD, 2010)

oddball: Spotting Anomalies in Weighted Graphs. - Leman Akoglu; Mary McGlohon; Christos Faloutsos (PAKDD (2), 2010)

Surprising Patterns for the Call Duration Distribution of Mobile Phone Users. - Pedro O. S. Vaz de Melo; Leman Akoglu; Christos Faloutsos; Antonio Alfredo Ferreira Loureiro (ECML/PKDD (3), 2010)

Statistical Properties of Social Networks. - Mary McGlohon; Leman Akoglu; Christos Faloutsos (Social Network Data Analytics, 2011)

It's who you know: graph mining using recursive structural features. - Keith Henderson; Brian Gallagher; Lei Li 005; Leman Akoglu; Tina Eliassi-Rad; Hanghang Tong; Christos Faloutsos (KDD, 2011)

Interactively and Visually Exploring Tours of Marked Nodes in Large Graphs. - Duen Horng Chau; Leman Akoglu; Jilles Vreeken; Hanghang Tong; Christos Faloutsos (ASONAM, 2012)

Fast and reliable anomaly detection in categorical data. - Leman Akoglu; Hanghang Tong; Jilles Vreeken; Christos Faloutsos (CIKM, 2012)

TourViz: interactive visualization of connection pathways in large graphs. - Duen Horng Chau; Leman Akoglu; Jilles Vreeken; Hanghang Tong; Christos Faloutsos (KDD, 2012)

RolX: structural role extraction & mining in large graphs. - Keith Henderson; Brian Gallagher; Tina Eliassi-Rad; Hanghang Tong; Sugato Basu; Leman Akoglu; Danai Koutra; Christos Faloutsos; Lei Li 005 (KDD, 2012)

Quantifying Reciprocity in Large Weighted Communication Networks. - Leman Akoglu; Pedro O. S. Vaz de Melo; Christos Faloutsos (PAKDD (2), 2012)

PICS: Parameter-free Identification of Cohesive Subgroups in Large Attributed Graphs. - Leman Akoglu; Hanghang Tong; Brendan Meeder; Christos Faloutsos (SDM, 2012)

OPAvion: mining and visualization in large graphs. - Leman Akoglu; Duen Horng Chau; U Kang; Danai Koutra; Christos Faloutsos (SIGMOD Conference, 2012)

Sex Differences in the Human Connectome. - Vivek Kulkarni; Jagat Sastry Pudipeddi; Leman Akoglu; Joshua T. Vogelstein; R. Jacob Vogelstein; Sephira Ryman; Rex E. Jung (Brain and Health Informatics, 2013)

Do more views of a graph help? Community detection and clustering in multi-graphs. - Evangelos E. Papalexakis; Leman Akoglu; Dino Ienco (FUSION, 2013)

External Evaluation of Topic Models: A Graph Mining Approach. - Hau Chan; Leman Akoglu (ICDM, 2013)

Opinion Fraud Detection in Online Reviews by Network Effects. - Leman Akoglu; Rishi Chandy; Christos Faloutsos (ICWSM, 2013)

Mining Connection Pathways for Marked Nodes in Large Graphs. - Leman Akoglu; Duen Horng Chau; Christos Faloutsos; Nikolaj Tatti; Hanghang Tong; Jilles Vreeken (SDM, 2013)

Anomaly, event, and fraud detection in large network datasets. - Leman Akoglu; Christos Faloutsos (WSDM, 2013)

Want a Good Answer? Ask a Good Question First! - Yuan Yao 001; Hanghang Tong; Tao Xie 001; Leman Akoglu; Feng Xu 007; Jian Lu 001 (CoRR, 2013)

ConnotationWordNet: Learning Connotation over the Word+Sense Network. - Jun Seok Kang; Song Feng 002; Leman Akoglu; Yejin Choi 001 (ACL (1), 2014)

Fast Information-Theoretic Agglomerative Co-clustering. - Tiantian Gao; Leman Akoglu (ADC, 2014)

Min(e)d your tags: Analysis of Question response time in StackOverflow. - Vasudev Bhat; Adheesh Gokhale; Ravi Jadhav; Jagat Sastry Pudipeddi; Leman Akoglu (ASONAM, 2014)

Joint voting prediction for questions and answers in CQA. - Yuan Yao 001; Hanghang Tong; Tao Xie 001; Leman Akoglu; Feng Xu 007; Jian Lu 001 (ASONAM, 2014)

Quantifying Political Polarity Based on Bipartite Opinion Networks. - Leman Akoglu (ICWSM, 2014)

Focused clustering and outlier detection in large attributed graphs. - Bryan Perozzi; Leman Akoglu; Patricia Iglesias Sánchez; Emmanuel Müller (KDD, 2014)

Fast Nearest Neighbor Search on Large Time-Evolving Graphs. - Leman Akoglu; Rohit Khandekar; Vibhore Kumar; Srinivasan Parthasarathy 002; Deepak Rajan; Kun-Lung Wu (ECML/PKDD (1), 2014)

Make It or Break It: Manipulating Robustness in Large Networks. - Hau Chan; Leman Akoglu; Hanghang Tong (SDM, 2014)

Big graph mining for the web and social media: algorithms, anomaly detection, and applications. - U Kang; Leman Akoglu; Duen Horng Chau (WSDM, 2014)

User churn in focused question answering sites: characterizations and prediction. - Jagat Sastry Pudipeddi; Leman Akoglu; Hanghang Tong (WWW (Companion Volume), 2014)

AFRAID: Fraud Detection via Active Inference in Time-evolving Social Networks. - Véronique Van Vlasselaer; Tina Eliassi-Rad; Leman Akoglu; Monique Snoeck; Bart Baesens (ASONAM, 2015)

Fraud Detection through Graph-Based User Behavior Modeling. - Alex Beutel; Leman Akoglu; Christos Faloutsos (CCS, 2015)

Guilt-by-Constellation: Fraud Detection by Suspicious Clique Memberships. - Véronique Van Vlasselaer; Leman Akoglu; Tina Eliassi-Rad; Monique Snoeck; Bart Baesens (HICSS, 2015)

Graph-Based User Behavior Modeling: From Prediction to Fraud Detection. - Alex Beutel; Leman Akoglu; Christos Faloutsos (KDD, 2015)

Collective Opinion Spam Detection: Bridging Review Networks and Metadata. - Shebuti Rayana; Leman Akoglu (KDD, 2015)

Discovering Opinion Spammer Groups by Network Footprints. - Junting Ye; Leman Akoglu (ECML/PKDD (1), 2015)

Where Graph Topology Matters: The Robust Subgraph Problem. - Hau Chan; Shuchu Han; Leman Akoglu (SDM, 2015)

Less is More: Building Selective Anomaly Ensembles with Application to Event Detection in Temporal Graphs. - Shebuti Rayana; Leman Akoglu (SDM, 2015)

Correlation of Node Importance Measures: An Empirical Study through Graph Robustness. - Mirza Basim Baig; Leman Akoglu (WWW (Companion Volume), 2015)

Robust Semi-Supervised Classification for Multi-Relational Graphs. - Junting Ye; Leman Akoglu (CoRR, 2015)

Graph based anomaly detection and description: a survey. - Leman Akoglu; Hanghang Tong; Danai Koutra (Data Min. Knowl. Discov., 2015)

APATE: A novel approach for automated credit card transaction fraud detection using network-based extensions. - Véronique Van Vlasselaer; Cristián Bravo; Olivier Caelen; Tina Eliassi-Rad; Leman Akoglu; Monique Snoeck; Bart Baesens (Decis. Support Syst., 2015)

Detecting high-quality posts in community question answering sites. - Yuan Yao 001; Hanghang Tong; Tao Xie 001; Leman Akoglu; Feng Xu 007; Jian Lu 001 (Inf. Sci., 2015)

Effects of tag usage on question response time - Analysis and prediction in StackOverflow. - Vasudev Bhat; Adheesh Gokhale; Ravi Jadhav; Jagat Sastry Pudipeddi; Leman Akoglu (Soc. Netw. Anal. Min., 2015)

ACM DAVA'16: 2nd International Workshop on DAta mining meets Visual Analytics at Big Data Era. - Lei Shi 002; Hanghang Tong; Chaoli Wang 001; Leman Akoglu (CIKM, 2016)

Sequential Ensemble Learning for Outlier Detection: A Bias-Variance Perspective. - Shebuti Rayana; Wen Zhong; Leman Akoglu (ICDM, 2016)

EdgeCentric: Anomaly Detection in Edge-Attributed Networks. - Neil Shah; Alex Beutel; Bryan Hooi; Leman Akoglu; Stephan Günnemann; Disha Makhija; Mohit Kumar 008; Christos Faloutsos (ICDM Workshops, 2016)

Temporal Opinion Spam Detection by Multivariate Indicative Signals. - Junting Ye; Santhosh Kumar; Leman Akoglu (ICWSM, 2016)

Fast Memory-efficient Anomaly Detection in Streaming Heterogeneous Graphs. - Emaad A. Manzoor; Sadegh M. Milajerdi; Leman Akoglu (KDD, 2016)

BIRDNEST: Bayesian Inference for Ratings-Fraud Detection. - Bryan Hooi; Neil Shah; Alex Beutel; Stephan Günnemann; Leman Akoglu; Mohit Kumar 008; Disha Makhija; Christos Faloutsos (SDM, 2016)

Scalable Anomaly Ranking of Attributed Neighborhoods. - Bryan Perozzi; Leman Akoglu (SDM, 2016)

Collective Opinion Spam Detection using Active Inference. - Shebuti Rayana; Leman Akoglu (SDM, 2016)

The Politics of Routing: Investigating the Relationship between AS Connectivity and Internet Freedom. - Rachee Singh; Hyungjoon Koo; Najmehalsadat Miramirkhani; Fahimeh Mirhaj; Phillipa Gill; Leman Akoglu (FOCI, 2016)

Fast Memory-efficient Anomaly Detection in Streaming Heterogeneous Graphs. - Emaad A. Manzoor; Sadegh Momeni; Venkat N. Venkatakrishnan; Leman Akoglu (CoRR, 2016)

Optimizing network robustness by edge rewiring: a general framework. - Hau Chan; Leman Akoglu (Data Min. Knowl. Discov., 2016)

Less is More: Building Selective Anomaly Ensembles. - Shebuti Rayana; Leman Akoglu (ACM Trans. Knowl. Discov. Data, 2016)

EIC Editorial. - Jian Pei 001; Leman Akoglu; Hongrae Lee; Justin J. Levandoski; Xuelong Li 001; Rosa Meo; Carlos Ordonez 001; Jeff M. Phillips; Barbara Poblete; K. Selçuk Candan; Meng Wang 001; Ji-Rong Wen; et al. (IEEE Trans. Knowl. Data Eng., 2016)

Online Detection of Anomalous Heterogeneous Graphs with Streaming Edges. - Leman Akoglu (ICDM Workshops, 2017)

RUSH!: Targeted Time-limited Coupons via Purchase Forecasts. - Emaad A. Manzoor; Leman Akoglu (KDD, 2017)

A Domain-Agnostic Approach to Spam-URL Detection via Redirects. - Heeyoung Kwon; Mirza Basim Baig; Leman Akoglu (PAKDD (2), 2017)

Ranking in Heterogeneous Networks with Geo-Location Information. - Abhinav Mishra; Leman Akoglu (SDM, 2017)

Ties That Bind: Characterizing Classes by Attributes and Social Ties. - Aria Rezaei; Bryan Perozzi; Leman Akoglu (WWW (Companion Volume), 2017)

Fast, Warped Graph Embedding: Unifying Framework and One-Click Algorithm. - Siheng Chen; Sufeng Niu; Leman Akoglu; Jelena Kovacevic; Christos Faloutsos (CoRR, 2017)

X-PACS: eXPlaining Anomalies by Characterizing Subspaces. - Meghanath Macha; Leman Akoglu (CoRR, 2017)

LookOut on Time-Evolving Graphs: Succinctly Explaining Anomalies from Any Detector. - Nikhil Gupta 007; Dhivya Eswaran; Neil Shah; Leman Akoglu; Christos Faloutsos (CoRR, 2017)

Automatic Detection of Online Recruitment Frauds: Characteristics, Methods, and a Public Dataset. - Sokratis Vidros; Constantinos Kolias; Georgios Kambourakis; Leman Akoglu (Future Internet, 2017)

GOTCHA! Network-Based Fraud Detection for Social Security Fraud. - Véronique Van Vlasselaer; Tina Eliassi-Rad; Leman Akoglu; Monique Snoeck; Bart Baesens (Manag. Sci., 2017)

A Lens into Employee Peer Reviews Via Sentiment-Aspect Modeling. - Abhinav Maurya; Leman Akoglu; Ramayya Krishnan; Daniel Bay (ASONAM, 2018)

ChangeDAR: Online Localized Change Detection for Sensor Data on a Graph. - Bryan Hooi; Leman Akoglu; Dhivya Eswaran; Amritanshu Pandey; Marko Jereminov; Larry T. Pileggi; Christos Faloutsos (CIKM, 2018)

A Quest for Structure: Jointly Learning the Graph Structure and Semi-Supervised Classification. - Xuan Wu; Lingxiao Zhao; Leman Akoglu (CIKM, 2018)

xStream: Outlier Detection in Feature-Evolving Data Streams. - Emaad A. Manzoor; Hemank Lamba; Leman Akoglu (KDD, 2018)

Robust Semi-Supervised Learning on Multiple Networks with Noise. - Junting Ye; Leman Akoglu (PAKDD (1), 2018)

Beyond Outlier Detection: LookOut for Pictorial Explanation. - Nikhil Gupta 007; Dhivya Eswaran; Neil Shah; Leman Akoglu; Christos Faloutsos (ECML/PKDD (1), 2018)

ConOut: Contextual Outlier Detection with Multiple Contexts: Application to Ad Fraud. - Meghanath Macha Yadagiri; Deepak Pai; Leman Akoglu (ECML/PKDD (1), 2018)

Incorporating Privileged Information to Unsupervised Anomaly Detection. - Shubhranshu Shekhar; Leman Akoglu (ECML/PKDD (1), 2018)

Explaining anomalies in groups with characterizing subspace rules. - Meghanath Macha; Leman Akoglu (Data Min. Knowl. Discov., 2018)

Discovering Communities and Anomalies in Attributed Graphs: Interactive Visual Exploration and Summarization. - Bryan Perozzi; Leman Akoglu (ACM Trans. Knowl. Discov. Data, 2018)

BuScope: Fusing Individual & Aggregated Mobility Behavior for. - Lakmal Meegahapola; Thivya Kandappu; Kasthuri Jayarajah; Leman Akoglu; Shili Xiang; Archan Misra (MobiSys, 2019)

Statistical Analysis of Nearest Neighbor Methods for Anomaly Detection. - Xiaoyi Gu; Leman Akoglu; Alessandro Rinaldo (NeurIPS, 2019)

Continual Rare-Class Recognition with Emerging Novel Subclasses. - Hung T. Nguyen 003; Xuejian Wang; Leman Akoglu (ECML/PKDD (2), 2019)

Bot Detection: Will Focusing on Recall Cause Overall Performance Deterioration? - Tahora H. Nazer; Matthew Davis; Mansooreh Karami; Leman Akoglu; David Koelle; Huan Liu 001 (SBP-BRiMS, 2019)

Learning On-the-Job to Re-rank Anomalies from Top-1 Feedback. - Hemank Lamba; Leman Akoglu (SDM, 2019)

ContraVis: Contrastive and Visual Topic Modeling for Comparing Document Collections. - Tuan M. V. Le; Leman Akoglu (WWW, 2019)

Coverage-based Outlier Explanation. - Yue Wu; Leman Akoglu; Ian Davidson (CoRR, 2019)

AutoAudit: Mining Accounting and Time-Evolving Graphs. - Meng-Chieh Lee; Yue Zhao 016; Aluna Wang; Pierre Jinghong Liang; Leman Akoglu; Vincent S. Tseng; Christos Faloutsos (IEEE BigData, 2020)

PairNorm: Tackling Oversmoothing in GNNs. - Lingxiao Zhao; Leman Akoglu (ICLR, 2020)

Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs. - Jiong Zhu; Yujun Yan; Lingxiao Zhao; Mark Heimann; Leman Akoglu; Danai Koutra (NeurIPS, 2020)

SUOD: A Scalable Unsupervised Outlier Detection Framework. - Yue Zhao 016; Xiyang Hu; Cheng Cheng 001; Cong Wang; Cao Xiao; Yunlong Wang 001; Jimeng Sun 001; Leman Akoglu (CoRR, 2020)

Generalizing Graph Neural Networks Beyond Homophily. - Jiong Zhu; Yujun Yan; Lingxiao Zhao; Mark Heimann; Leman Akoglu; Danai Koutra (CoRR, 2020)

Connecting Graph Convolutional Networks and Graph-Regularized PCA. - Lingxiao Zhao; Leman Akoglu (CoRR, 2020)

Automating Outlier Detection via Meta-Learning. - Yue Zhao 016; Ryan A. Rossi; Leman Akoglu (CoRR, 2020)

Anomaly Detection in Large Labeled Multi-Graph Databases. - Hung T. Nguyen 003; Pierre J. Liang; Leman Akoglu (CoRR, 2020)

End-to-End Continual Rare-Class Recognition with Emerging Novel Subclasses. - Hung T. Nguyen 003; Xuejian Wang; Leman Akoglu (ACM Trans. Knowl. Discov. Data, 2020)

FairOD: Fairness-aware Outlier Detection. - Shubhranshu Shekhar; Neil Shah; Leman Akoglu (AIES, 2021)

GAWD: graph anomaly detection in weighted directed graph databases. - Meng-Chieh Lee; Hung T. Nguyen 003; Dimitris Berberidis; Vincent S. Tseng; Leman Akoglu (ASONAM, 2021)

Anomaly Mining: Past, Present and Future. - Leman Akoglu (CIKM, 2021)

Fast Attributed Graph Embedding via Density of States. - Saurabh Sawlani; Lingxiao Zhao; Leman Akoglu (ICDM, 2021)

ODD: Outlier Detection and Description. - Siddharth Bhatia 001; Bryan Hooi; Leman Akoglu; Sourav Chatterjee; Xiaodong Jiang; Manish Gupta (KDD, 2021)

Machine Learning in Finance. - Senthil Kumar; Leman Akoglu; Nitesh V. Chawla; José A. Rodríguez-Serrano; Tanveer A. Faruquie; Saurabh Nagrecha (KDD, 2021)

SUOD: Accelerating Large-Scale Unsupervised Heterogeneous Outlier Detection. - Yue Zhao 016; Xiyang Hu; Cheng Cheng 001; Cong Wang; Changlin Wan; Wen Wang; Jianing Yang; Haoping Bai; Zheng Li; Cao Xiao; Yunlong Wang 001; Zhi Qiao 007; et al. (MLSys, 2021)

Automatic Unsupervised Outlier Model Selection. - Yue Zhao 016; Ryan A. Rossi; Leman Akoglu (NeurIPS, 2021)

A Large-scale Study on Unsupervised Outlier Model Selection: Do Internal Strategies Suffice? - Martin Q. Ma; Yue Zhao 016; Xiaorong Zhang; Leman Akoglu (CoRR, 2021)

Detecting Changed-Hands Online Review Accounts. - Geli Fei; Shuai Wang 020; Bing Liu 001; Leman Akoglu (CoRR, 2021)

C-AllOut: Catching & Calling Outliers by Type. - Guilherme D. F. Silva; Leman Akoglu; Robson L. F. Cordeiro (CoRR, 2021)

Toward Unsupervised Outlier Model Selection. - Yue Zhao 016; Sean Zhang; Leman Akoglu (ICDM, 2022)

D.MCA: Outlier Detection with Explicit Micro-Cluster Assignments. - Shuli Jiang; Robson L. F. Cordeiro; Leman Akoglu (ICDM, 2022)

From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness. - Lingxiao Zhao; Wei Jin 009; Leman Akoglu; Neil Shah (ICLR, 2022)

KDD Workshop on Machine Learning in Finance. - Senthil Kumar; Leman Akoglu; Nitesh V. Chawla; Saurabh Nagrecha; Vidyut M. Naware; Tanveer A. Faruquie; Hays McCormick (KDD, 2022)

Sparx: Distributed Outlier Detection at Scale. - Sean Zhang; Varun Ursekar; Leman Akoglu (KDD, 2022)

Hyperparameter Sensitivity in Deep Outlier Detection: Analysis and a Scalable Hyper-Ensemble Solution. - Xueying Ding; Lingxiao Zhao; Leman Akoglu (NeurIPS, 2022)

Dual-discriminative Graph Neural Network for Imbalanced Graph-level Anomaly Detection. - Ge Zhang 002; Zhenyu Yang 004; Jia Wu 001; Jian Yang 001; Shan Xue 001; Hao Peng 001; Jianlin Su; Chuan Zhou 001; Quan Z. Sheng; Leman Akoglu; Charu C. Aggarwal (NeurIPS, 2022)

A Practical, Progressively-Expressive GNN. - Lingxiao Zhao; Neil Shah; Leman Akoglu (NeurIPS, 2022)

Summarizing Labeled Multi-graphs. - Dimitris Berberidis; Pierre J. Liang; Leman Akoglu (ECML/PKDD (2), 2022)

Understanding the Effect of Data Augmentation in Self-supervised Anomaly Detection. - Jaemin Yoo; Tiancheng Zhao; Leman Akoglu (CoRR, 2022)

Towards Unsupervised HPO for Outlier Detection. - Yue Zhao 016; Leman Akoglu (CoRR, 2022)

A Practical, Progressively-Expressive GNN. - Lingxiao Zhao; Louis Härtel; Neil Shah; Leman Akoglu (CoRR, 2022)

Graph Anomaly Detection with Unsupervised GNNs. - Lingxiao Zhao; Saurabh Sawlani; Arvind Srinivasan 002; Leman Akoglu (CoRR, 2022)

Unsupervised Machine Learning for Explainable Medicare Fraud Detection. - Shubhranshu Shekhar; Jetson Leder-Luis; Leman Akoglu (CoRR, 2022)

ACM WSDM 2022 report. - K. Selçuk Candan; Huan Liu 001; Leman Akoglu; Xin Luna Dong; Jiliang Tang; Andrew Tomkins (SIGWEB Newsl., 2022)

Self-Supervision for Tackling Unsupervised Anomaly Detection: Pitfalls and Opportunities. - Leman Akoglu; Jaemin Yoo (IEEE Big Data, 2023)

ADAMM: Anomaly Detection of Attributed Multi-graphs with Metadata: A Unified Neural Network Approach. - Konstantinos Sotiropoulos; Lingxiao Zhao; Pierre Jinghong Liang; Leman Akoglu (IEEE Big Data, 2023)

From Detection to Action: a Human-in-the-loop Toolkit for Anomaly Reasoning and Management. - Xueying Ding; Nikita Seleznev; Senthil Kumar; C. Bayan Bruss; Leman Akoglu (ICAIF, 2023)

KDD Workshop on Machine Learning in Finance. - Leman Akoglu; Nitesh V. Chawla; Senthil Kumar; Saurabh Nagrecha; Mahashweta Das; Vidyut M. Naware; Tanveer A. Faruquie (KDD, 2023)

19th International Workshop on Mining and Learning with Graphs (MLG). - Neil Shah; Shobeir Fakhraei; Da Zheng; Bahare Fatemi; Leman Akoglu (KDD, 2023)

DSV: An Alignment Validation Loss for Self-supervised Outlier Model Selection. - Jaemin Yoo; Yue Zhao 016; Lingxiao Zhao; Leman Akoglu (ECML/PKDD (1), 2023)

From Explanation to Action: An End-to-End Human-in-the-loop Framework for Anomaly Reasoning and Management. - Xueying Ding; Nikita Seleznev; Senthil Kumar; C. Bayan Bruss; Leman Akoglu (CoRR, 2023)

End-to-End Augmentation Hyperparameter Tuning for Self-Supervised Anomaly Detection. - Jaemin Yoo; Lingxiao Zhao; Leman Akoglu (CoRR, 2023)

Heterophily and Graph Neural Networks: Past, Present and Future. - Jiong Zhu; Yujun Yan; Mark Heimann; Lingxiao Zhao; Leman Akoglu; Danai Koutra (IEEE Data Eng. Bull., 2023)

Deep Anomaly Analytics: Advancing the Frontier of Anomaly Detection. - Feng Xia 001; Leman Akoglu; Charu Aggarwal 001; Huan Liu 001 (IEEE Intell. Syst., 2023)

The Need for Unsupervised Outlier Model Selection: A Review and Evaluation of Internal Evaluation Strategies. - Martin Q. Ma; Yue Zhao 016; Xiaorong Zhang; Leman Akoglu (SIGKDD Explor., 2023)

Data Augmentation is a Hyperparameter: Cherry-picked Self-Supervision for Unsupervised Anomaly Detection is Creating the Illusion of Success. - Jaemin Yoo; Tiancheng Zhao; Leman Akoglu (Trans. Mach. Learn. Res., 2023)

Detecting Anomalous Graphs in Labeled Multi-Graph Databases. - Hung T. Nguyen 003; Pierre J. Liang; Leman Akoglu (ACM Trans. Knowl. Discov. Data, 2023)

Benefit-aware early prediction of health outcomes on multivariate EEG time series. - Shubhranshu Shekhar; Dhivya Eswaran; Bryan Hooi; Jonathan Elmer; Christos Faloutsos; Leman Akoglu (J. Biomed. Informatics, 2023)

On Using Classification Datasets to Evaluate Graph Outlier Detection: Peculiar Observations and New Insights. - Lingxiao Zhao; Leman Akoglu (Big Data, 2023)

Density of states for fast embedding node-attributed graphs. - Lingxiao Zhao; Saurabh Sawlani; Leman Akoglu (Knowl. Inf. Syst., 2023)

A Comprehensive Survey on Graph Anomaly Detection With Deep Learning. - Xiaoxiao Ma 002; Jia Wu 001; Shan Xue 001; Jian Yang 001; Chuan Zhou 001; Quan Z. Sheng; Hui Xiong 001; Leman Akoglu (IEEE Trans. Knowl. Data Eng., 2023)

Outlier Detection Bias Busted: Understanding Sources of Algorithmic Bias through Data-centric Factors. - Xueying Ding; Rui Xi; Leman Akoglu (AIES (1), 2024)

HPOD: Hyperparameter Optimization for Unsupervised Outlier Detection. - Yue Zhao 016; Leman Akoglu (AutoML, 2024)

Machine Learning in Finance. - Leman Akoglu; Nitesh V. Chawla; Josep Domingo-Ferrer; Eren Kurshan; Senthil Kumar; Vidyut M. Naware; José A. Rodríguez-Serrano; Isha Chaturvedi; Saurabh Nagrecha; Mahashweta Das; Tanveer A. Faruquie (KDD, 2024)

Fast Unsupervised Deep Outlier Model Selection with Hypernetworks. - Xueying Ding; Yue Zhao 016; Leman Akoglu (KDD, 2024)

Pard: Permutation-Invariant Autoregressive Diffusion for Graph Generation. - Lingxiao Zhao; Xueying Ding; Leman Akoglu (NeurIPS, 2024)

Descriptive Kernel Convolution Network with Improved Random Walk Kernel. - Meng-Chieh Lee; Lingxiao Zhao; Leman Akoglu (WWW, 2024)

Improving and Unifying Discrete&Continuous-time Discrete Denoising Diffusion. - Lingxiao Zhao; Xueying Ding; Lijun Yu; Leman Akoglu (CoRR, 2024)

End-To-End Self-tuning Self-supervised Time Series Anomaly Detection. - Boje Deforce; Meng-Chieh Lee; Bart Baesens; Estefanía Serral Asensio; Jaemin Yoo; Leman Akoglu (CoRR, 2024)

Zero-shot Outlier Detection via Prior-data Fitted Networks: Model Selection Bygone! - Yuchen Shen; Haomin Wen; Leman Akoglu (CoRR, 2024)

Uncertainty-aware Human Mobility Modeling and Anomaly Detection. - Haomin Wen; Shurui Cao; Leman Akoglu (CoRR, 2024)

Trajectory Anomaly Detection with By-Design Complementary Detectors. - Shurui Cao; Leman Akoglu (SDM, 2025)

End-To-End Self-Tuning Self-Supervised Time Series Anomaly Detection. - Boje Deforce; Meng-Chieh Lee; Bart Baesens; Estefanía Serrai Asensio; Jaemin Yoo; Leman Akoglu (SDM, 2025)

On the Detection of Reviewer-Author Collusion Rings From Paper Bidding. - Steven Jecmen; Nihar B. Shah; Fei Fang 001; Leman Akoglu (Trans. Mach. Learn. Res., 2025)

CoBAD: Modeling Collective Behaviors for Human Mobility Anomaly Detection. - Haomin Wen; Shurui Cao; Leman Akoglu (CoRR, 2025)