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2020 – today
- 2025
[j15]Farhat Lamia Barsha, William Eberle:
An in-depth review and analysis of mode collapse in generative adversarial networks. Mach. Learn. 114(6): 141 (2025)- 2024
- [j14]Ingrid Russell, Sheikh Rabiul Islam, William Eberle, Douglas A. Talbert, Md Golam Moula Mehedi Hasan:
Preface. Int. J. Artif. Intell. Tools 33(3): 2402001:1-2402001:3 (2024) - [j13]Sheikh Rabiul Islam, Ingrid Russell, William Eberle, Douglas A. Talbert, Md Golam Moula Mehedi Hasan:
Advances in Explainable, Fair, and Trustworthy AI. Int. J. Artif. Intell. Tools 33(3): 2403001:1-2403001:5 (2024) - [j12]Ocheme Anthony Ekle
, William Eberle:
Anomaly Detection in Dynamic Graphs: A Comprehensive Survey. ACM Trans. Knowl. Discov. Data 18(8): 192:1-192:44 (2024) - [c52]Farhat Lamia Barsha, William Eberle:
Mode Collapse Detection Strategies in Generative Adversarial Networks for Credit Card Fraud Detection. FLAIRS 2024 - [c51]Ocheme Anthony Ekle, William Eberle:
Dynamic PageRank with Decay: A Modified Approach for Node Anomaly Detection in Evolving Graph Streams. FLAIRS 2024 - [i9]Prabin B. Lamichhane, William Eberle:
Anomaly Detection in Graph Structured Data: A Survey. CoRR abs/2405.06172 (2024) - [i8]Ocheme Anthony Ekle, William Eberle:
Anomaly Detection in Dynamic Graphs: A Comprehensive Survey. CoRR abs/2406.00134 (2024) - 2022
- [j11]Sheikh Rabiul Islam, Ingrid Russell, William Eberle, Darina Dicheva:
Instilling conscience about bias and fairness in automated decisions. J. Comput. Sci. Coll. 37(8): 22-31 (2022) - [c50]Prabin B. Lamichhane, Hannah Mannering, William Eberle:
Discovering Breach Patterns on the Internet of Health Things: A Graph and Machine Learning Anomaly Analysis. FLAIRS 2022 - [c49]Prabin B. Lamichhane, William Eberle:
Self-Organizing Map-Based Graph Clustering and Visualization on Streaming Graphs. ICDM (Workshops) 2022: 706-713 - [c48]Sheikh Rabiul Islam, Ingrid Russell, William Eberle, Darina Dicheva:
Incorporating the Concepts of Fairness and Bias into an Undergraduate Computer Science Course to Promote Fair Automated Decision Systems. SIGCSE (2) 2022: 1075 - 2021
- [c47]Sheikh Rabiul Islam, William Eberle:
Implications of Combining Domain Knowledge in Explainable Artificial Intelligence. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering 2021 - [c46]Prabin B. Lamichhane, William Eberle:
Anomaly Detection in Edge Streams Using Term Frequency-Inverse Graph Frequency (TF-IGF) Concept. IEEE BigData 2021: 661-667 - [c45]Ramesh Paudel, Lauren Tharp, Dulce Kaiser, William Eberle, Gerald C. Gannod:
Visualization of Anomalies using Graph-Based Anomaly Detection. FLAIRS 2021 - [i7]Sheikh Rabiul Islam, William Eberle, Sheikh Khaled Ghafoor, Mohiuddin Ahmed:
Explainable Artificial Intelligence Approaches: A Survey. CoRR abs/2101.09429 (2021) - 2020
- [j10]Ramesh Paudel, William Eberle:
An Approach For Concept Drift Detection in a Graph Stream Using Discriminative Subgraphs. ACM Trans. Knowl. Discov. Data 14(6): 70:1-70:25 (2020) - [c44]Sheikh Rabiul Islam, William Eberle, Sheikh K. Ghafoor, Ambareen Siraj, Mike Rogers:
Domain Knowledge Aided Explainable Artificial Intelligence for Intrusion Detection and Response. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (1) 2020 - [c43]William Eberle, Lawrence Holder:
Graph Filtering to Remove the "Middle Ground" for Anomaly Detection. IEEE BigData 2020: 2947-2956 - [c42]Sheikh Rabiul Islam, William Eberle, Sheikh K. Ghafoor:
Towards Quantification of Explainability in Explainable Artificial Intelligence Methods. FLAIRS 2020: 75-81 - [c41]Prajjwal Kandel, William Eberle:
Node Similarity For Anomaly Detection in Attributed Graphs. FLAIRS 2020: 82-87
2010 – 2019
- 2019
- [c40]Ramesh Paudel, Timothy Muncy, William Eberle:
Detecting DoS Attack in Smart Home IoT Devices Using a Graph-Based Approach. IEEE BigData 2019: 5249-5258 - [c39]Ramesh Paudel, Peter Harlan, William Eberle:
Detecting the Onset of a Network Layer DoS Attack with a Graph-Based Approach. FLAIRS 2019: 38-43 - [c38]Farzana Ahamed Bhuiyan, Md Bulbul Sharif, Paul Joshua Tinker, William Eberle, Douglas A. Talbert, Sheikh Khaled Ghafoor, Lewis J. Frey:
Gene Selection and Clustering of Breast Cancer Data. FLAIRS 2019: 287-292 - [c37]Sirisha Velampalli, Lenin Mookiah, William Eberle:
Discovering Suspicious Patterns Using a Graph Based Approach. FLAIRS 2019: 382-386 - [i6]Sheikh Rabiul Islam, William Eberle, Sid C. Bundy, Sheikh Khaled Ghafoor:
Infusing domain knowledge in AI-based "black box" models for better explainability with application in bankruptcy prediction. CoRR abs/1905.11474 (2019) - [i5]Sheikh Rabiul Islam, William Eberle, Sheikh K. Ghafoor, Ambareen Siraj, Mike Rogers:
Domain Knowledge Aided Explainable Artificial Intelligence for Intrusion Detection and Response. CoRR abs/1911.09853 (2019) - [i4]Sheikh Rabiul Islam, William Eberle, Sheikh K. Ghafoor, Sid C. Bundy, Douglas A. Talbert, Ambareen Siraj:
Investigating bankruptcy prediction models in the presence of extreme class imbalance and multiple stages of economy. CoRR abs/1911.09858 (2019) - [i3]Sheikh Rabiul Islam, William Eberle, Sheikh K. Ghafoor:
Towards Quantification of Explainability in Explainable Artificial Intelligence Methods. CoRR abs/1911.10104 (2019) - 2018
- [j9]Lenin Mookiah, William Eberle, Maitrayi Mondal:
Personalized news recommendation using graph-based approach. Intell. Data Anal. 22(4): 881-909 (2018) - [j8]Deron Liang, Chih-Fong Tsai, An-Jie Dai, William Eberle:
A novel classifier ensemble approach for financial distress prediction. Knowl. Inf. Syst. 54(2): 437-462 (2018) - [c36]Sheikh Rabiul Islam, Sheikh Khaled Ghafoor, William Eberle:
Mining Illegal Insider Trading of Stocks: A Proactive Approach. IEEE BigData 2018: 1397-1406 - [c35]Ramesh Paudel, Kimberlyn Dunn, William Eberle, Danielle Chaung:
Cognitive Health Prediction on the Elderly Using Sensor Data in Smart Homes. FLAIRS 2018: 317-322 - [c34]David Bisant, William Eberle:
Special Track on Data Mining. FLAIRS 2018: 403 - [c33]Rina Singh, Jeffrey A. Graves, Douglas A. Talbert, William Eberle:
Prefix and Suffix Sequential Pattern Mining. ICDM 2018: 309-324 - [c32]Rina Singh, Jeffrey A. Graves, Douglas A. Talbert, William Eberle:
Prefix and Suffix Sequential Pattern Mining. MLDM (1) 2018: 296-311 - [i2]Sheikh Rabiul Islam, William Eberle, Sheikh Khaled Ghafoor:
Mining Bad Credit Card Accounts from OLAP and OLTP. CoRR abs/1807.00819 (2018) - [i1]Sheikh Rabiul Islam, William Eberle, Sheikh Khaled Ghafoor:
Credit Default Mining Using Combined Machine Learning and Heuristic Approach. CoRR abs/1807.01176 (2018) - 2017
- [c31]Lenin Mookiah, Chris Dean, William Eberle:
Graph-Based Anomaly Detection on Smart Grid Data. FLAIRS 2017: 306-311 - [c30]Ramesh Paudel, William Eberle, Douglas A. Talbert:
Detection of Anomalous Activity in Diabetic Patients Using Graph-Based Approach. FLAIRS 2017: 423-429 - [c29]Sirisha Velampalli, William Eberle:
Novel Graph Based Anomaly Detection Using Background Knowledge. FLAIRS 2017: 538-543 - [c28]Nishith Mukeshkumar Thakkar, Lenin Mookiah, Douglas A. Talbert, William Eberle:
Anomalies in Students Enrollment Using Visualization. FLAIRS 2017: 544-548 - [c27]Sheikh Rabiul Islam, William Eberle, Sheikh Khaled Ghafoor:
Mining Bad Credit Card Accounts from OLAP and OLTP. ICCDA 2017: 129-137 - [c26]Sirisha Velampalli, Lenin Mookiah, William Eberle:
Detecting Vehicular Patterns Using a Graph-Based Approach. VAST 2017: 209-210 - 2016
- [j7]Zdravko Markov, Ingrid Russell, William Eberle:
Report on the 29th International Florida Artificial Intelligence Research Society Conference (FLAIRS-29). AI Mag. 37(4): 81-82 (2016) - [j6]Min-Wei Huang, Wei-Chao Lin, Chih-Wen Chen, Shih-Wen Ke, Chih-Fong Tsai, William Eberle:
Data preprocessing issues for incomplete medical datasets. Expert Syst. J. Knowl. Eng. 33(5): 432-438 (2016) - [c25]Douglas A. Talbert, William Eberle, Mei Liu:
Never-Ending Medical Learning. AMIA 2016 - 2015
- [j5]William Eberle, Lawrence B. Holder:
Scalable anomaly detection in graphs. Intell. Data Anal. 19(1): 57-74 (2015) - [j4]Wei-Chao Lin, Chih-Fong Tsai, Shih-Wen Ke, Chia-Wen Hung, William Eberle:
Learning to detect representative data for large scale instance selection. J. Syst. Softw. 106: 1-8 (2015) - [j3]Zong-Yao Chen, Chih-Fong Tsai, William Eberle, Wei-Chao Lin, Shih-Wen Ke:
Instance selection by genetic-based biological algorithm. Soft Comput. 19(5): 1269-1282 (2015) - [c24]Cameron Chaparro, William Eberle:
Detecting Anomalies in Mobile Telecommunication Networks Using a Graph Based Approach. FLAIRS 2015: 410-415 - [c23]Lenin Mookiah, William Eberle, Larry Holder:
Discovering Suspicious Behavior Using Graph-Based Approach. FLAIRS 2015: 428-433 - [c22]Lenin Mookiah, William Eberle, Ambareen Siraj:
Survey of Crime Analysis and Prediction. FLAIRS 2015: 440-443 - [e2]Ingrid Russell, William Eberle:
Proceedings of the Twenty-Eighth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2015, Hollywood, Florida, USA, May 18-20, 2015. AAAI Press 2015 [contents] - 2014
- [c21]William Eberle, Lawrence B. Holder:
A partitioning approach to scaling anomaly detection in graph streams. IEEE BigData 2014: 17-24 - [c20]Vitaly Ford, Ambareen Siraj, William Eberle:
Smart grid energy fraud detection using artificial neural networks. CIASG 2014: 91-96 - [c19]David Bisant, William Eberle:
Special Track on Data Mining. FLAIRS 2014 - [c18]Lenin Mookiah, William Eberle, Lawrence B. Holder:
Detecting suspicious behavior using a graph-based approach. IEEE VAST 2014: 357-358 - [e1]William Eberle, Chutima Boonthum-Denecke:
Proceedings of the Twenty-Seventh International Florida Artificial Intelligence Research Society Conference, FLAIRS 2014, Pensacola Beach, Florida, USA, May 21-23, 2014. AAAI Press 2014, ISBN 978-1-57735-658-5 [contents] - 2013
- [j2]Chih-Fong Tsai, William Eberle, Chi-Yuan Chu:
Genetic algorithms in feature and instance selection. Knowl. Based Syst. 39: 240-247 (2013) - [c17]Christopher J. Morack, William Eberle:
Computer science widening the STEM education spectrum. FIE 2013: 1329-1335 - [c16]William Eberle, John Karro, Neal Lerner, Matthias F. Stallmann:
Integrating communication skills in data structures and algorithms courses. FIE 2013: 1503-1509 - [c15]David Bisant, William Eberle:
Special Track on Data Mining. FLAIRS 2013 - [c14]Alan Matthew McCormick, William Eberle:
Discovering Fraud in Online Classified Ads. FLAIRS 2013 - [c13]William Eberle, Lawrence B. Holder:
Incremental Anomaly Detection in Graphs. ICDM Workshops 2013: 521-528 - 2012
- [c12]William Eberle, Lawrence B. Holder, Beverly Massengill:
Graph-Based Anomaly Detection Applied to Homeland Security Cargo Screening. FLAIRS 2012 - 2011
- [c11]David Bisant, William Eberle:
Special Track on Data Mining. FLAIRS 2011 - [c10]William Eberle, Lawrence B. Holder:
Graph-Based Knowledge Discovery: Compression versus Frequency. FLAIRS 2011 - 2010
- [c9]William Eberle, Lawrence B. Holder, Jeffrey Graves:
Using a Graph-Based Approach for Discovering Cybercrime. FLAIRS 2010
2000 – 2009
- 2009
- [c8]William Eberle, Lawrence B. Holder:
Mining for insider threats in business transactions and processes. CIDM 2009: 163-170 - [c7]William Eberle, Lawrence B. Holder:
Graph-based approaches to insider threat detection. CSIIRW 2009: 44 - [c6]William Eberle, David Bisant:
Special Track on Data Mining. FLAIRS 2009 - [c5]William Eberle, Lawrence B. Holder:
Discovering Anomalies to Multiple Normative Patterns in Structural and Numeric Data. FLAIRS 2009 - [c4]William Eberle, Lawrence B. Holder:
Applying graph-based anomaly detection approaches to the discovery of insider threats. ISI 2009: 206-208 - 2007
- [j1]William Eberle, Lawrence B. Holder:
Anomaly detection in data represented as graphs. Intell. Data Anal. 11(6): 663-689 (2007) - [c3]William Eberle, Lawrence B. Holder:
Mining for Structural Anomalies in Graph-based Data. DMIN 2007: 376-389 - [c2]William Eberle, Lawrence B. Holder:
Discovering Structural Anomalies in Graph-Based Data. ICDM Workshops 2007: 393-398 - 2006
- [c1]William Eberle, Lawrence B. Holder:
Detecting Anomalies in Cargo Using Graph Properties. ISI 2006: 728-730
Coauthor Index
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last updated on 2025-05-17 00:27 CEST by the dblp team
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