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ORCIDLeman Akoglu
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2020 – today
- 2024
[c102]Xueying Ding
, Yue Zhao, Leman Akoglu:
Fast Unsupervised Deep Outlier Model Selection with Hypernetworks. KDD 2024: 585-596- [c101]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: 6703 - [c100]Meng-Chieh Lee, Lingxiao Zhao, Leman Akoglu:
Descriptive Kernel Convolution Network with Improved Random Walk Kernel. WWW 2024: 457-468 - [e3]Luz Angelica Caudillo-Mata, Silvio Lattanzi, Andrés Muñoz Medina, Leman Akoglu, Aristides Gionis, Sergei Vassilvitskii:
Proceedings of the 17th ACM International Conference on Web Search and Data Mining, WSDM 2024, Merida, Mexico, March 4-8, 2024. ACM 2024 [contents] - [i61]Lingxiao Zhao, Xueying Ding, Leman Akoglu:
Pard: Permutation-Invariant Autoregressive Diffusion for Graph Generation. CoRR abs/2402.03687 (2024) - [i60]Lingxiao Zhao, Xueying Ding, Lijun Yu, Leman Akoglu:
Improving and Unifying Discrete&Continuous-time Discrete Denoising Diffusion. CoRR abs/2402.03701 (2024) - [i59]Meng-Chieh Lee, Lingxiao Zhao, Leman Akoglu:
Descriptive Kernel Convolution Network with Improved Random Walk Kernel. CoRR abs/2402.06087 (2024) - [i58]Steven Jecmen, Nihar B. Shah, Fei Fang, Leman Akoglu:
On the Detection of Reviewer-Author Collusion Rings From Paper Bidding. CoRR abs/2402.07860 (2024) - [i57]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 abs/2404.02865 (2024) - [i56]Xueying Ding, Rui Xi, Leman Akoglu:
Outlier Detection Bias Busted: Understanding Sources of Algorithmic Bias through Data-centric Factors. CoRR abs/2408.13667 (2024) - [i55]Yuchen Shen, Haomin Wen, Leman Akoglu:
Zero-shot Outlier Detection via Prior-data Fitted Networks: Model Selection Bygone! CoRR abs/2409.05672 (2024) - [i54]Haomin Wen, Shurui Cao, Leman Akoglu:
Uncertainty-aware Human Mobility Modeling and Anomaly Detection. CoRR abs/2410.01281 (2024) - 2023
- [j23]Lingxiao Zhao, Leman Akoglu:
On Using Classification Datasets to Evaluate Graph Outlier Detection: Peculiar Observations and New Insights. Big Data 11(3): 151-180 (2023) - [j22]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): 12-34 (2023) - [j21]Feng Xia, Leman Akoglu, Charu Aggarwal, Huan Liu:
Deep Anomaly Analytics: Advancing the Frontier of Anomaly Detection. IEEE Intell. Syst. 38(2): 32-35 (2023) - [j20]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: 104296 (2023) - [j19]Lingxiao Zhao, Saurabh Sawlani, Leman Akoglu:
Density of states for fast embedding node-attributed graphs. Knowl. Inf. Syst. 65(6): 2455-2483 (2023) - [j18]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): 19-35 (2023) - [j17]Hung T. Nguyen, Pierre J. Liang, Leman Akoglu:
Detecting Anomalous Graphs in Labeled Multi-Graph Databases. ACM Trans. Knowl. Discov. Data 17(2): 16:1-16:25 (2023) - [j16]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): 12012-12038 (2023) - [j15]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) - [c99]Konstantinos Sotiropoulos, Lingxiao Zhao, Pierre Jinghong Liang, Leman Akoglu:
ADAMM: Anomaly Detection of Attributed Multi-graphs with Metadata: A Unified Neural Network Approach. IEEE Big Data 2023: 865-874 - [c98]Leman Akoglu, Jaemin Yoo:
Self-Supervision for Tackling Unsupervised Anomaly Detection: Pitfalls and Opportunities. IEEE Big Data 2023: 1047-1051 - [c97]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: 279-287 - [c96]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: 5863-5864 - [c95]Neil Shah, Shobeir Fakhraei, Da Zheng, Bahare Fatemi, Leman Akoglu:
19th International Workshop on Mining and Learning with Graphs (MLG). KDD 2023: 5882-5883 - [c94]Jaemin Yoo, Yue Zhao, Lingxiao Zhao, Leman Akoglu:
DSV: An Alignment Validation Loss for Self-supervised Outlier Model Selection. ECML/PKDD (1) 2023: 254-269 - [e2]Ambuj K. Singh, Yizhou Sun, Leman Akoglu, Dimitrios Gunopulos, Xifeng Yan, Ravi Kumar, Fatma Ozcan, Jieping Ye:
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2023, Long Beach, CA, USA, August 6-10, 2023. ACM 2023 [contents] - [i53]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 abs/2304.03368 (2023) - [i52]Jaemin Yoo, Lingxiao Zhao, Leman Akoglu:
End-to-End Augmentation Hyperparameter Tuning for Self-Supervised Anomaly Detection. CoRR abs/2306.12033 (2023) - [i51]Jaemin Yoo, Yue Zhao, Lingxiao Zhao, Leman Akoglu:
DSV: An Alignment Validation Loss for Self-supervised Outlier Model Selection. CoRR abs/2307.06534 (2023) - [i50]Xueying Ding, Yue Zhao, Leman Akoglu:
Fast Unsupervised Deep Outlier Model Selection with Hypernetworks. CoRR abs/2307.10529 (2023) - [i49]Leman Akoglu, Jaemin Yoo:
Self-Supervision for Tackling Unsupervised Anomaly Detection: Pitfalls and Opportunities. CoRR abs/2308.14380 (2023) - [i48]Konstantinos Sotiropoulos, Lingxiao Zhao, Pierre Jinghong Liang, Leman Akoglu:
ADAMM: Anomaly Detection of Attributed Multi-graphs with Metadata: A Unified Neural Network Approach. CoRR abs/2311.07355 (2023) - 2022
- [j14]K. Selçuk Candan, Huan Liu, Leman Akoglu, Xin Luna Dong, Jiliang Tang, Andrew Tomkins:
ACM WSDM 2022 report. SIGWEB Newsl. 2022(Summer): 1:1-1:6 (2022) - [c93]Yue Zhao, Sean Zhang, Leman Akoglu:
Toward Unsupervised Outlier Model Selection. ICDM 2022: 773-782 - [c92]Shuli Jiang, Robson L. F. Cordeiro, Leman Akoglu:
D.MCA: Outlier Detection with Explicit Micro-Cluster Assignments. ICDM 2022: 987-992 - [c91]Lingxiao Zhao, Wei Jin, Leman Akoglu, Neil Shah:
From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness. ICLR 2022 - [c90]Sean Zhang, Varun Ursekar, Leman Akoglu:
Sparx: Distributed Outlier Detection at Scale. KDD 2022: 4530-4540 - [c89]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: 4882-4883 - [c88]Xueying Ding, Lingxiao Zhao, Leman Akoglu:
Hyperparameter Sensitivity in Deep Outlier Detection: Analysis and a Scalable Hyper-Ensemble Solution. NeurIPS 2022 - [c87]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 - [c86]Lingxiao Zhao, Neil Shah, Leman Akoglu:
A Practical, Progressively-Expressive GNN. NeurIPS 2022 - [c85]Dimitris Berberidis, Pierre J. Liang, Leman Akoglu:
Summarizing Labeled Multi-graphs. ECML/PKDD (2) 2022: 53-68 - [e1]K. Selcuk Candan, Huan Liu, Leman Akoglu, Xin Luna Dong, Jiliang Tang:
WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21 - 25, 2022. ACM 2022, ISBN 978-1-4503-9132-0 [contents] - [i47]Sean Zhang, Varun Ursekar, Leman Akoglu:
Sparx: Distributed Outlier Detection at Scale. CoRR abs/2206.01281 (2022) - [i46]Xueying Ding, Lingxiao Zhao, Leman Akoglu:
Hyperparameter Sensitivity in Deep Outlier Detection: Analysis and a Scalable Hyper-Ensemble Solution. CoRR abs/2206.07647 (2022) - [i45]Dimitris Berberidis, Pierre J. Liang, Leman Akoglu:
Summarizing Labeled Multi-Graphs. CoRR abs/2206.07674 (2022) - [i44]Jaemin Yoo, Tiancheng Zhao, Leman Akoglu:
Understanding the Effect of Data Augmentation in Self-supervised Anomaly Detection. CoRR abs/2208.07734 (2022) - [i43]Yue Zhao, Leman Akoglu:
Towards Unsupervised HPO for Outlier Detection. CoRR abs/2208.11727 (2022) - [i42]Shuli Jiang, Robson Leonardo Ferreira Cordeiro, Leman Akoglu:
D.MCA: Outlier Detection with Explicit Micro-Cluster Assignments. CoRR abs/2210.08212 (2022) - [i41]Lingxiao Zhao, Louis Härtel, Neil Shah, Leman Akoglu:
A Practical, Progressively-Expressive GNN. CoRR abs/2210.09521 (2022) - [i40]Lingxiao Zhao, Saurabh Sawlani, Arvind Srinivasan, Leman Akoglu:
Graph Anomaly Detection with Unsupervised GNNs. CoRR abs/2210.09535 (2022) - [i39]Yue Zhao, Sean Zhang, Leman Akoglu:
Toward Unsupervised Outlier Model Selection. CoRR abs/2211.01834 (2022) - [i38]Shubhranshu Shekhar, Jetson Leder-Luis, Leman Akoglu:
Unsupervised Machine Learning for Explainable Medicare Fraud Detection. CoRR abs/2211.02927 (2022) - 2021
- [c84]Shubhranshu Shekhar, Neil Shah, Leman Akoglu:
FairOD: Fairness-aware Outlier Detection. AIES 2021: 210-220 - [c83]Meng-Chieh Lee, Hung T. Nguyen, Dimitris Berberidis, Vincent S. Tseng, Leman Akoglu:
GAWD: graph anomaly detection in weighted directed graph databases. ASONAM 2021: 143-150 - [c82]Leman Akoglu:
Anomaly Mining: Past, Present and Future. CIKM 2021: 1-2 - [c81]Saurabh Sawlani, Lingxiao Zhao, Leman Akoglu:
Fast Attributed Graph Embedding via Density of States. ICDM 2021: 559-568 - [c80]Leman Akoglu:
Anomaly Mining - Past, Present and Future. IJCAI 2021: 4932-4936 - [c79]Siddharth Bhatia, Bryan Hooi, Leman Akoglu, Sourav Chatterjee, Xiaodong Jiang, Manish Gupta:
ODD: Outlier Detection and Description. KDD 2021: 4108-4109 - [c78]Senthil Kumar, Leman Akoglu, Nitesh V. Chawla, José A. Rodríguez-Serrano, Tanveer A. Faruquie, Saurabh Nagrecha:
Machine Learning in Finance. KDD 2021: 4139-4140 - [c77]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 - [c76]Yue Zhao, Ryan A. Rossi, Leman Akoglu:
Automatic Unsupervised Outlier Model Selection. NeurIPS 2021: 4489-4502 - [i37]Martin Q. Ma, Yue Zhao, Xiaorong Zhang, Leman Akoglu:
A Large-scale Study on Unsupervised Outlier Model Selection: Do Internal Strategies Suffice? CoRR abs/2104.01422 (2021) - [i36]Leman Akoglu:
Anomaly Mining - Past, Present and Future. CoRR abs/2105.10077 (2021) - [i35]Geli Fei, Shuai Wang, Bing Liu, Leman Akoglu:
Detecting Changed-Hands Online Review Accounts. CoRR abs/2106.15352 (2021) - [i34]Lingxiao Zhao, Wei Jin, Leman Akoglu, Neil Shah:
From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness. CoRR abs/2110.03753 (2021) - [i33]Saurabh Sawlani, Lingxiao Zhao, Leman Akoglu:
Fast Attributed Graph Embedding via Density of States. CoRR abs/2110.05228 (2021) - [i32]Guilherme D. F. Silva, Leman Akoglu, Robson L. F. Cordeiro:
C-AllOut: Catching & Calling Outliers by Type. CoRR abs/2110.08257 (2021) - [i31]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 abs/2111.06032 (2021) - 2020
- [j13]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): 61:1-61:28 (2020) - [c75]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: 950-956 - [c74]Lingxiao Zhao, Leman Akoglu:
PairNorm: Tackling Oversmoothing in GNNs. ICLR 2020 - [c73]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 - [i30]Yue Zhao, Xiyang Hu, Cheng Cheng, Cong Wang, Cao Xiao, Yunlong Wang, Jimeng Sun, Leman Akoglu:
SUOD: A Scalable Unsupervised Outlier Detection Framework. CoRR abs/2003.05731 (2020) - [i29]Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu, Danai Koutra:
Generalizing Graph Neural Networks Beyond Homophily. CoRR abs/2006.11468 (2020) - [i28]Lingxiao Zhao, Leman Akoglu:
Connecting Graph Convolutional Networks and Graph-Regularized PCA. CoRR abs/2006.12294 (2020) - [i27]Yue Zhao, Ryan A. Rossi, Leman Akoglu:
Automating Outlier Detection via Meta-Learning. CoRR abs/2009.10606 (2020) - [i26]Hung T. Nguyen, Pierre J. Liang, Leman Akoglu:
Anomaly Detection in Large Labeled Multi-Graph Databases. CoRR abs/2010.03600 (2020) - [i25]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 abs/2011.00447 (2020) - [i24]Shubhranshu Shekhar, Neil Shah, Leman Akoglu:
FAIROD: Fairness-aware Outlier Detection. CoRR abs/2012.03063 (2020) - [i23]Lingxiao Zhao, Leman Akoglu:
On Using Classification Datasets to Evaluate Graph Outlier Detection: Peculiar Observations and New Insights. CoRR abs/2012.12931 (2020)
2010 – 2019
- 2019
- [c72]Lakmal Meegahapola, Thivya Kandappu, Kasthuri Jayarajah, Leman Akoglu, Shili Xiang, Archan Misra:
BuScope: Fusing Individual & Aggregated Mobility Behavior for. MobiSys 2019: 41-53 - [c71]Xiaoyi Gu, Leman Akoglu, Alessandro Rinaldo:
Statistical Analysis of Nearest Neighbor Methods for Anomaly Detection. NeurIPS 2019: 10921-10931 - [c70]Hung T. Nguyen, Xuejian Wang, Leman Akoglu:
Continual Rare-Class Recognition with Emerging Novel Subclasses. ECML/PKDD (2) 2019: 20-36 - [c69]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: 39-49 - [c68]Hemank Lamba, Leman Akoglu:
Learning On-the-Job to Re-rank Anomalies from Top-1 Feedback. SDM 2019: 612-620 - [c67]Tuan M. V. Le, Leman Akoglu:
ContraVis: Contrastive and Visual Topic Modeling for Comparing Document Collections. WWW 2019: 928-938 - [i22]Hung T. Nguyen, Xuejian Wang, Leman Akoglu:
Continual Rare-Class Recognition with Emerging Novel Subclasses. CoRR abs/1906.12218 (2019) - [i21]Xiaoyi Gu, Leman Akoglu, Alessandro Rinaldo:
Statistical Analysis of Nearest Neighbor Methods for Anomaly Detection. CoRR abs/1907.03813 (2019) - [i20]Lingxiao Zhao, Leman Akoglu:
PairNorm: Tackling Oversmoothing in GNNs. CoRR abs/1909.12223 (2019) - [i19]Xuan Wu, Lingxiao Zhao, Leman Akoglu:
A Quest for Structure: Jointly Learning the Graph Structure and Semi-Supervised Classification. CoRR abs/1909.12385 (2019) - [i18]Yue Wu, Leman Akoglu, Ian Davidson:
Coverage-based Outlier Explanation. CoRR abs/1911.02617 (2019) - 2018
- [j12]Meghanath Macha, Leman Akoglu:
Explaining anomalies in groups with characterizing subspace rules. Data Min. Knowl. Discov. 32(5): 1444-1480 (2018) - [j11]Bryan Perozzi, Leman Akoglu:
Discovering Communities and Anomalies in Attributed Graphs: Interactive Visual Exploration and Summarization. ACM Trans. Knowl. Discov. Data 12(2): 24:1-24:40 (2018) - [c66]Abhinav Maurya, Leman Akoglu, Ramayya Krishnan, Daniel Bay:
A Lens into Employee Peer Reviews Via Sentiment-Aspect Modeling. ASONAM 2018: 670-677 - [c65]Xuan Wu, Lingxiao Zhao, Leman Akoglu:
A Quest for Structure: Jointly Learning the Graph Structure and Semi-Supervised Classification. CIKM 2018: 87-96 - [c64]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: 507-516 - [c63]Emaad A. Manzoor, Hemank Lamba, Leman Akoglu:
xStream: Outlier Detection in Feature-Evolving Data Streams. KDD 2018: 1963-1972 - [c62]Junting Ye, Leman Akoglu:
Robust Semi-Supervised Learning on Multiple Networks with Noise. PAKDD (1) 2018: 196-208 - [c61]Shubhranshu Shekhar, Leman Akoglu:
Incorporating Privileged Information to Unsupervised Anomaly Detection. ECML/PKDD (1) 2018: 87-104 - [c60]Nikhil Gupta, Dhivya Eswaran, Neil Shah, Leman Akoglu, Christos Faloutsos:
Beyond Outlier Detection: LookOut for Pictorial Explanation. ECML/PKDD (1) 2018: 122-138 - [c59]Meghanath Macha Yadagiri, Deepak Pai, Leman Akoglu:
ConOut: Contextual Outlier Detection with Multiple Contexts: Application to Ad Fraud. ECML/PKDD (1) 2018: 139-156 - [i17]Shubhranshu Shekhar, Leman Akoglu:
Incorporating Privileged Information to Unsupervised Anomaly Detection. CoRR abs/1805.02269 (2018) - 2017
- [j10]Sokratis Vidros, Constantinos Kolias, Georgios Kambourakis, Leman Akoglu:
Automatic Detection of Online Recruitment Frauds: Characteristics, Methods, and a Public Dataset. Future Internet 9(1): 6 (2017) - [j9]Véronique Van Vlasselaer, Tina Eliassi-Rad, Leman Akoglu, Monique Snoeck, Bart Baesens:
GOTCHA! Network-Based Fraud Detection for Social Security Fraud. Manag. Sci. 63(9): 3090-3110 (2017) - [c58]Leman Akoglu:
Online Detection of Anomalous Heterogeneous Graphs with Streaming Edges. ICDM Workshops 2017: 968 - [c57]Emaad A. Manzoor, Leman Akoglu:
RUSH!: Targeted Time-limited Coupons via Purchase Forecasts. KDD 2017: 1923-1931 - [c56]Heeyoung Kwon, Mirza Basim Baig, Leman Akoglu:
A Domain-Agnostic Approach to Spam-URL Detection via Redirects. PAKDD (2) 2017: 220-232 - [c55]Abhinav Mishra, Leman Akoglu:
Ranking in Heterogeneous Networks with Geo-Location Information. SDM 2017: 408-416 - [c54]Aria Rezaei, Bryan Perozzi, Leman Akoglu:
Ties That Bind: Characterizing Classes by Attributes and Social Ties. WWW (Companion Volume) 2017: 973-981 - [i16]Aria Rezaei, Bryan Perozzi, Leman Akoglu:
Ties That Bind - Characterizing Classes by Attributes and Social Ties. CoRR abs/1701.09039 (2017) - [i15]Siheng Chen, Sufeng Niu, Leman Akoglu, Jelena Kovacevic, Christos Faloutsos:
Fast, Warped Graph Embedding: Unifying Framework and One-Click Algorithm. CoRR abs/1702.05764 (2017) - [i14]Meghanath Macha, Leman Akoglu:
X-PACS: eXPlaining Anomalies by Characterizing Subspaces. CoRR abs/1708.05929 (2017) - [i13]Nikhil Gupta, Dhivya Eswaran, Neil Shah, Leman Akoglu, Christos Faloutsos:
LookOut on Time-Evolving Graphs: Succinctly Explaining Anomalies from Any Detector. CoRR abs/1710.05333 (2017) - 2016
- [j8]Hau Chan, Leman Akoglu:
Optimizing network robustness by edge rewiring: a general framework. Data Min. Knowl. Discov. 30(5): 1395-1425 (2016) - [j7]Shebuti Rayana, Leman Akoglu:
Less is More: Building Selective Anomaly Ensembles. ACM Trans. Knowl. Discov. Data 10(4): 42:1-42:33 (2016) - [j6]