Leman Akoglu

ORCID

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 127

Top Venues

Publications

Lingxiao Zhao, Xueying Ding, Lijun Yu, Leman Akoglu
Improving and Unifying Discrete&Continuous-time Discrete Denoising Diffusion. CoRR (2024)
Boje Deforce, Meng-Chieh Lee, Bart Baesens, Estefanía Serral Asensio, Jaemin Yoo, Leman Akoglu
End-To-End Self-tuning Self-supervised Time Series Anomaly Detection. CoRR (2024)
Lingxiao Zhao, Xueying Ding, Leman Akoglu
Pard: Permutation-Invariant Autoregressive Diffusion for Graph Generation. CoRR (2024)
Steven Jecmen, Nihar B. Shah, Fei Fang, Leman Akoglu
On the Detection of Reviewer-Author Collusion Rings From Paper Bidding. CoRR (2024)
Xueying Ding, Yue Zhao, Leman Akoglu
Fast Unsupervised Deep Outlier Model Selection with Hypernetworks. KDD (2024)
Meng-Chieh Lee, Lingxiao Zhao, Leman Akoglu
Descriptive Kernel Convolution Network with Improved Random Walk Kernel. CoRR (2024)
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
Machine Learning in Finance. KDD (2024)
Meng-Chieh Lee, Lingxiao Zhao, Leman Akoglu
Descriptive Kernel Convolution Network with Improved Random Walk Kernel. WWW (2024)
Xueying Ding, Yue Zhao, Leman Akoglu
Fast Unsupervised Deep Outlier Model Selection with Hypernetworks. CoRR (2023)
Jaemin Yoo, Tiancheng Zhao, Leman Akoglu
Data Augmentation is a Hyperparameter: Cherry-picked Self-Supervision for Unsupervised Anomaly Detection is Creating the Illusion of Success. Trans. Mach. Learn. Res. 2023 (2023)
Leman Akoglu, Jaemin Yoo
Self-Supervision for Tackling Unsupervised Anomaly Detection: Pitfalls and Opportunities. CoRR (2023)
Leman Akoglu, Jaemin Yoo
Self-Supervision for Tackling Unsupervised Anomaly Detection: Pitfalls and Opportunities. BigData (2023)
Neil Shah, Shobeir Fakhraei, Da Zheng, Bahare Fatemi, Leman Akoglu
19th International Workshop on Mining and Learning with Graphs (MLG). KDD (2023)
Xueying Ding, Nikita Seleznev, Senthil Kumar, C. Bayan Bruss, Leman Akoglu
From Explanation to Action: An End-to-End Human-in-the-loop Framework for Anomaly Reasoning and Management. CoRR (2023)
Lingxiao Zhao, Leman Akoglu
On Using Classification Datasets to Evaluate Graph Outlier Detection: Peculiar Observations and New Insights. Big Data 11 (3) (2023)
Feng Xia, Leman Akoglu, Charu Aggarwal, Huan Liu
Deep Anomaly Analytics: Advancing the Frontier of Anomaly Detection. IEEE Intell. Syst. 38 (2) (2023)
Jaemin Yoo, Yue Zhao, Lingxiao Zhao, Leman Akoglu
DSV: An Alignment Validation Loss for Self-supervised Outlier Model Selection. CoRR (2023)
Xueying Ding, Nikita Seleznev, Senthil Kumar, C. Bayan Bruss, Leman Akoglu
From Detection to Action: a Human-in-the-loop Toolkit for Anomaly Reasoning and Management. ICAIF (2023)
Martin Q. Ma, Yue Zhao, Xiaorong Zhang, Leman Akoglu
The Need for Unsupervised Outlier Model Selection: A Review and Evaluation of Internal Evaluation Strategies. SIGKDD Explor. 25 (1) (2023)
Jiong Zhu, Yujun Yan, Mark Heimann, Lingxiao Zhao, Leman Akoglu, Danai Koutra
Heterophily and Graph Neural Networks: Past, Present and Future. IEEE Data Eng. Bull. 46 (2) (2023)
Konstantinos Sotiropoulos, Lingxiao Zhao, Pierre Jinghong Liang, Leman Akoglu
ADAMM: Anomaly Detection of Attributed Multi-graphs with Metadata: A Unified Neural Network Approach. CoRR (2023)
Hung T. Nguyen, Pierre J. Liang, Leman Akoglu
Detecting Anomalous Graphs in Labeled Multi-Graph Databases. ACM Trans. Knowl. Discov. Data 17 (2) (2023)
Jaemin Yoo, Lingxiao Zhao, Leman Akoglu
End-to-End Augmentation Hyperparameter Tuning for Self-Supervised Anomaly Detection. CoRR (2023)
Jaemin Yoo, Yue Zhao, Lingxiao Zhao, Leman Akoglu
DSV: An Alignment Validation Loss for Self-supervised Outlier Model Selection. ECML/PKDD (1) (2023)
Konstantinos Sotiropoulos, Lingxiao Zhao, Pierre Jinghong Liang, Leman Akoglu
ADAMM: Anomaly Detection of Attributed Multi-graphs with Metadata: A Unified Neural Network Approach. BigData (2023)
Lingxiao Zhao, Saurabh Sawlani, Leman Akoglu
Density of states for fast embedding node-attributed graphs. Knowl. Inf. Syst. 65 (6) (2023)
Shubhranshu Shekhar, Dhivya Eswaran, Bryan Hooi, Jonathan Elmer, Christos Faloutsos, Leman Akoglu
Benefit-aware early prediction of health outcomes on multivariate EEG time series. J. Biomed. Informatics 139 (2023)
Leman Akoglu, Nitesh V. Chawla, Senthil Kumar, Saurabh Nagrecha, Mahashweta Das, Vidyut M. Naware, Tanveer A. Faruquie
KDD Workshop on Machine Learning in Finance. KDD (2023)
Xiaoxiao Ma, Jia Wu, Shan Xue, Jian Yang, Chuan Zhou, Quan Z. Sheng, Hui Xiong, Leman Akoglu
A Comprehensive Survey on Graph Anomaly Detection With Deep Learning. IEEE Trans. Knowl. Data Eng. 35 (12) (2023)
K. Selçuk Candan, Huan Liu, Leman Akoglu, Xin Luna Dong, Jiliang Tang, Andrew Tomkins
ACM WSDM 2022 report. SIGWEB Newsl. 2022 (Summer) (2022)
Sean Zhang, Varun Ursekar, Leman Akoglu
Sparx: Distributed Outlier Detection at Scale. KDD (2022)
Shuli Jiang, Robson L. F. Cordeiro, Leman Akoglu
D.MCA: Outlier Detection with Explicit Micro-Cluster Assignments. ICDM (2022)
Shubhranshu Shekhar, Jetson Leder-Luis, Leman Akoglu
Unsupervised Machine Learning for Explainable Medicare Fraud Detection. CoRR (2022)
Lingxiao Zhao, Wei Jin, Leman Akoglu, Neil Shah
From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness. ICLR (2022)
Xueying Ding, Lingxiao Zhao, Leman Akoglu
Hyperparameter Sensitivity in Deep Outlier Detection: Analysis and a Scalable Hyper-Ensemble Solution. NeurIPS (2022)
Sean Zhang, Varun Ursekar, Leman Akoglu
Sparx: Distributed Outlier Detection at Scale. CoRR (2022)
Dimitris Berberidis, Pierre J. Liang, Leman Akoglu
Summarizing Labeled Multi-Graphs. CoRR (2022)
Yue Zhao, Sean Zhang, Leman Akoglu
Toward Unsupervised Outlier Model Selection. ICDM (2022)
Shuli Jiang, Robson Leonardo Ferreira Cordeiro, Leman Akoglu
D.MCA: Outlier Detection with Explicit Micro-Cluster Assignments. CoRR (2022)
Lingxiao Zhao, Saurabh Sawlani, Arvind Srinivasan, Leman Akoglu
Graph Anomaly Detection with Unsupervised GNNs. CoRR (2022)
Dimitris Berberidis, Pierre J. Liang, Leman Akoglu
Summarizing Labeled Multi-graphs. ECML/PKDD (2) (2022)
Senthil Kumar, Leman Akoglu, Nitesh V. Chawla, Saurabh Nagrecha, Vidyut M. Naware, Tanveer A. Faruquie, Hays McCormick
KDD Workshop on Machine Learning in Finance. KDD (2022)
Yue Zhao, Leman Akoglu
Towards Unsupervised HPO for Outlier Detection. CoRR (2022)
Xueying Ding, Lingxiao Zhao, Leman Akoglu
Hyperparameter Sensitivity in Deep Outlier Detection: Analysis and a Scalable Hyper-Ensemble Solution. CoRR (2022)
Lingxiao Zhao, Neil Shah, Leman Akoglu
A Practical, Progressively-Expressive GNN. NeurIPS (2022)
Yue Zhao, Sean Zhang, Leman Akoglu
Toward Unsupervised Outlier Model Selection. CoRR (2022)
Lingxiao Zhao, Louis Härtel, Neil Shah, Leman Akoglu
A Practical, Progressively-Expressive GNN. CoRR (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)
Jaemin Yoo, Tiancheng Zhao, Leman Akoglu
Understanding the Effect of Data Augmentation in Self-supervised Anomaly Detection. CoRR (2022)
Yue Zhao, Xiyang Hu, Cheng Cheng, Cong Wang, Changlin Wan, Wen Wang, Jianing Yang, Haoping Bai, Zheng Li, Cao Xiao, Yunlong Wang, Zhi Qiao, Jimeng Sun, Leman Akoglu
SUOD: Accelerating Large-Scale Unsupervised Heterogeneous Outlier Detection. MLSys (2021)
Saurabh Sawlani, Lingxiao Zhao, Leman Akoglu
Fast Attributed Graph Embedding via Density of States. ICDM (2021)
Geli Fei, Shuai Wang, Bing Liu, Leman Akoglu
Detecting Changed-Hands Online Review Accounts. CoRR (2021)
Shubhranshu Shekhar, Dhivya Eswaran, Bryan Hooi, Jonathan Elmer, Christos Faloutsos, Leman Akoglu
Benefit-aware Early Prediction of Health Outcomes on Multivariate EEG Time Series. CoRR (2021)
Senthil Kumar, Leman Akoglu, Nitesh V. Chawla, José A. Rodríguez-Serrano, Tanveer A. Faruquie, Saurabh Nagrecha
Machine Learning in Finance. KDD (2021)
Siddharth Bhatia, Bryan Hooi, Leman Akoglu, Sourav Chatterjee, Xiaodong Jiang, Manish Gupta
ODD: Outlier Detection and Description. KDD (2021)
Yue Zhao, Ryan A. Rossi, Leman Akoglu
Automatic Unsupervised Outlier Model Selection. NeurIPS (2021)
Lingxiao Zhao, Wei Jin, Leman Akoglu, Neil Shah
From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness. CoRR (2021)
Leman Akoglu
Anomaly Mining: Past, Present and Future. CIKM (2021)
Meng-Chieh Lee, Hung T. Nguyen, Dimitris Berberidis, Vincent S. Tseng, Leman Akoglu
GAWD: graph anomaly detection in weighted directed graph databases. ASONAM (2021)
Leman Akoglu
Anomaly Mining - Past, Present and Future. IJCAI (2021)
Saurabh Sawlani, Lingxiao Zhao, Leman Akoglu
Fast Attributed Graph Embedding via Density of States. CoRR (2021)
Guilherme D. F. Silva, Leman Akoglu, Robson L. F. Cordeiro
C-AllOut: Catching & Calling Outliers by Type. CoRR (2021)
Shubhranshu Shekhar, Neil Shah, Leman Akoglu
FairOD: Fairness-aware Outlier Detection. AIES (2021)
Leman Akoglu
Anomaly Mining - Past, Present and Future. CoRR (2021)
Martin Q. Ma, Yue Zhao, Xiaorong Zhang, Leman Akoglu
A Large-scale Study on Unsupervised Outlier Model Selection: Do Internal Strategies Suffice? CoRR (2021)
Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu, Danai Koutra
Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs. NeurIPS (2020)
Lingxiao Zhao, Leman Akoglu
PairNorm: Tackling Oversmoothing in GNNs. ICLR (2020)
Lingxiao Zhao, Leman Akoglu
Connecting Graph Convolutional Networks and Graph-Regularized PCA. CoRR (2020)
Yue Zhao, Ryan A. Rossi, Leman Akoglu
Automating Outlier Detection via Meta-Learning. CoRR (2020)
Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu, Danai Koutra
Generalizing Graph Neural Networks Beyond Homophily. CoRR (2020)
Yue Zhao, Xiyang Hu, Cheng Cheng, Cong Wang, Cao Xiao, Yunlong Wang, Jimeng Sun, Leman Akoglu
SUOD: A Scalable Unsupervised Outlier Detection Framework. CoRR (2020)
Lingxiao Zhao, Leman Akoglu
On Using Classification Datasets to Evaluate Graph Outlier Detection: Peculiar Observations and New Insights. CoRR (2020)
Hung T. Nguyen, Xuejian Wang, Leman Akoglu
End-to-End Continual Rare-Class Recognition with Emerging Novel Subclasses. ACM Trans. Knowl. Discov. Data 14 (5) (2020)
Hung T. Nguyen, Pierre J. Liang, Leman Akoglu
Anomaly Detection in Large Labeled Multi-Graph Databases. CoRR (2020)
Meng-Chieh Lee, Yue Zhao, Aluna Wang, Pierre Jinghong Liang, Leman Akoglu, Vincent S. Tseng, Christos Faloutsos
AutoAudit: Mining Accounting and Time-Evolving Graphs. CoRR (2020)
Meng-Chieh Lee, Yue Zhao, Aluna Wang, Pierre Jinghong Liang, Leman Akoglu, Vincent S. Tseng, Christos Faloutsos
AutoAudit: Mining Accounting and Time-Evolving Graphs. IEEE BigData (2020)
Shubhranshu Shekhar, Neil Shah, Leman Akoglu
FAIROD: Fairness-aware Outlier Detection. CoRR (2020)
Tahora H. Nazer, Matthew Davis, Mansooreh Karami, Leman Akoglu, David Koelle, Huan Liu
Bot Detection: Will Focusing on Recall Cause Overall Performance Deterioration? SBP-BRiMS (2019)
Xiaoyi Gu, Leman Akoglu, Alessandro Rinaldo
Statistical Analysis of Nearest Neighbor Methods for Anomaly Detection. NeurIPS (2019)
Lakmal Meegahapola, Thivya Kandappu, Kasthuri Jayarajah, Leman Akoglu, Shili Xiang, Archan Misra
BuScope: Fusing Individual & Aggregated Mobility Behavior for. MobiSys (2019)
Xuan Wu, Lingxiao Zhao, Leman Akoglu
A Quest for Structure: Jointly Learning the Graph Structure and Semi-Supervised Classification. CoRR (2019)
Yue Wu, Leman Akoglu, Ian Davidson
Coverage-based Outlier Explanation. CoRR (2019)
Xiaoyi Gu, Leman Akoglu, Alessandro Rinaldo
Statistical Analysis of Nearest Neighbor Methods for Anomaly Detection. CoRR (2019)
Hemank Lamba, Leman Akoglu
Learning On-the-Job to Re-rank Anomalies from Top-1 Feedback. SDM (2019)
Tuan M. V. Le, Leman Akoglu
ContraVis: Contrastive and Visual Topic Modeling for Comparing Document Collections. WWW (2019)
Hung T. Nguyen, Xuejian Wang, Leman Akoglu
Continual Rare-Class Recognition with Emerging Novel Subclasses. CoRR (2019)
Lingxiao Zhao, Leman Akoglu
PairNorm: Tackling Oversmoothing in GNNs. CoRR (2019)
Hung T. Nguyen, Xuejian Wang, Leman Akoglu
Continual Rare-Class Recognition with Emerging Novel Subclasses. ECML/PKDD (2) (2019)
Emaad A. Manzoor, Hemank Lamba, Leman Akoglu
xStream: Outlier Detection in Feature-Evolving Data Streams. KDD (2018)
Abhinav Maurya, Leman Akoglu, Ramayya Krishnan, Daniel Bay
A Lens into Employee Peer Reviews Via Sentiment-Aspect Modeling. ASONAM (2018)
Nikhil Gupta, Dhivya Eswaran, Neil Shah, Leman Akoglu, Christos Faloutsos
Beyond Outlier Detection: LookOut for Pictorial Explanation. ECML/PKDD (1) (2018)
Bryan Perozzi, Leman Akoglu
Discovering Communities and Anomalies in Attributed Graphs: Interactive Visual Exploration and Summarization. ACM Trans. Knowl. Discov. Data 12 (2) (2018)
Meghanath Macha Meghanath, Deepak Pai, Leman Akoglu
ConOut: Contextual Outlier Detection with Multiple Contexts: Application to Ad Fraud. ECML/PKDD (1) (2018)
Xuan Wu, Lingxiao Zhao, Leman Akoglu
A Quest for Structure: Jointly Learning the Graph Structure and Semi-Supervised Classification. CIKM (2018)
Meghanath Macha, Leman Akoglu
Explaining anomalies in groups with characterizing subspace rules. Data Min. Knowl. Discov. 32 (5) (2018)
Bryan Hooi, Leman Akoglu, Dhivya Eswaran, Amritanshu Pandey, Marko Jereminov, Larry T. Pileggi, Christos Faloutsos
ChangeDAR: Online Localized Change Detection for Sensor Data on a Graph. CIKM (2018)
Junting Ye, Leman Akoglu
Robust Semi-Supervised Learning on Multiple Networks with Noise. PAKDD (1) (2018)
Shubhranshu Shekhar, Leman Akoglu
Incorporating Privileged Information to Unsupervised Anomaly Detection. ECML/PKDD (1) (2018)
Shubhranshu Shekhar, Leman Akoglu
Incorporating Privileged Information to Unsupervised Anomaly Detection. CoRR (2018)
Abhinav Mishra, Leman Akoglu
Ranking in Heterogeneous Networks with Geo-Location Information. SDM (2017)

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Publication Activity (10 Years)

Top Topics

Top Venues

Leman Akoglu