Detecting Anomalies in Cargo Using Graph Properties. - William Eberle; Lawrence B. Holder (ISI, 2006)

Mining for Structural Anomalies in Graph-based Data. - William Eberle; Lawrence B. Holder (DMIN, 2007)

Discovering Structural Anomalies in Graph-Based Data. - William Eberle; Lawrence B. Holder (ICDM Workshops, 2007)

Anomaly detection in data represented as graphs. - William Eberle; Lawrence B. Holder (Intell. Data Anal., 2007)

Mining for insider threats in business transactions and processes. - William Eberle; Lawrence B. Holder (CIDM, 2009)

Graph-based approaches to insider threat detection. - William Eberle; Lawrence B. Holder (CSIIRW, 2009)

Discovering Anomalies to Multiple Normative Patterns in Structural and Numeric Data. - William Eberle; Lawrence B. Holder (FLAIRS, 2009)

Applying graph-based anomaly detection approaches to the discovery of insider threats. - William Eberle; Lawrence B. Holder (ISI, 2009)

Using a Graph-Based Approach for Discovering Cybercrime. - William Eberle; Lawrence B. Holder; Jeffrey Graves (FLAIRS, 2010)

Graph-Based Knowledge Discovery: Compression versus Frequency. - William Eberle; Lawrence B. Holder (FLAIRS, 2011)

Graph-Based Anomaly Detection Applied to Homeland Security Cargo Screening. - William Eberle; Lawrence B. Holder; Beverly Massengill (FLAIRS, 2012)

Integrating communication skills in data structures and algorithms courses. - William Eberle; John Karro; Neal Lerner; Matthias F. Stallmann (FIE, 2013)

Computer science widening the STEM education spectrum. - Christopher J. Morack; William Eberle (FIE, 2013)

Special Track on Data Mining. - David Bisant; William Eberle (FLAIRS, 2013)

Discovering Fraud in Online Classified Ads. - Alan Matthew McCormick; William Eberle (FLAIRS, 2013)

Incremental Anomaly Detection in Graphs. - William Eberle; Lawrence B. Holder (ICDM Workshops, 2013)

Genetic algorithms in feature and instance selection. - Chih-Fong Tsai; William Eberle; Chi-Yuan Chu (Knowl. Based Syst., 2013)

A partitioning approach to scaling anomaly detection in graph streams. - William Eberle; Lawrence B. Holder (IEEE BigData, 2014)

Smart grid energy fraud detection using artificial neural networks. - Vitaly Ford; Ambareen Siraj; William Eberle (CIASG, 2014)

Detecting suspicious behavior using a graph-based approach. - Lenin Mookiah; William Eberle; Lawrence B. Holder (IEEE VAST, 2014)

Detecting Anomalies in Mobile Telecommunication Networks Using a Graph Based Approach. - Cameron Chaparro; William Eberle (FLAIRS, 2015)

Discovering Suspicious Behavior Using Graph-Based Approach. - Lenin Mookiah; William Eberle; Larry Holder (FLAIRS, 2015)

Survey of Crime Analysis and Prediction. - Lenin Mookiah; William Eberle; Ambareen Siraj (FLAIRS, 2015)

Scalable anomaly detection in graphs. - William Eberle; Lawrence B. Holder (Intell. Data Anal., 2015)

Learning to detect representative data for large scale instance selection. - Wei-Chao Lin; Chih-Fong Tsai; Shih-Wen Ke; Chia-Wen Hung; William Eberle (J. Syst. Softw., 2015)

Instance selection by genetic-based biological algorithm. - Zong-Yao Chen; Chih-Fong Tsai; William Eberle; Wei-Chao Lin; Shih-Wen Ke (Soft Comput., 2015)

Never-Ending Medical Learning. - Douglas A. Talbert; William Eberle; Mei Liu (AMIA, 2016)

Report on the 29th International Florida Artificial Intelligence Research Society Conference (FLAIRS-29). - Zdravko Markov; Ingrid Russell; William Eberle (AI Mag., 2016)

Data preprocessing issues for incomplete medical datasets. - Min-Wei Huang; Wei-Chao Lin; Chih-Wen Chen; Shih-Wen Ke; Chih-Fong Tsai; William Eberle (Expert Syst. J. Knowl. Eng., 2016)

Graph-Based Anomaly Detection on Smart Grid Data. - Lenin Mookiah; Chris Dean; William Eberle (FLAIRS, 2017)

Detection of Anomalous Activity in Diabetic Patients Using Graph-Based Approach. - Ramesh Paudel; William Eberle; Douglas A. Talbert (FLAIRS, 2017)

Anomalies in Students Enrollment Using Visualization. - Nishith Mukeshkumar Thakkar; Lenin Mookiah; Douglas A. Talbert; William Eberle (FLAIRS, 2017)

Novel Graph Based Anomaly Detection Using Background Knowledge. - Sirisha Velampalli; William Eberle (FLAIRS, 2017)

Mining Bad Credit Card Accounts from OLAP and OLTP. - Sheikh Rabiul Islam; William Eberle; Sheikh Khaled Ghafoor (ICCDA, 2017)

Detecting Vehicular Patterns Using a Graph-Based Approach. - Sirisha Velampalli; Lenin Mookiah; William Eberle (VAST, 2017)

Mining Illegal Insider Trading of Stocks: A Proactive Approach. - Sheikh Rabiul Islam; Sheikh Khaled Ghafoor; William Eberle (IEEE BigData, 2018)

Cognitive Health Prediction on the Elderly Using Sensor Data in Smart Homes. - Ramesh Paudel; Kimberlyn Dunn; William Eberle; Danielle Chaung (FLAIRS, 2018)

Prefix and Suffix Sequential Pattern Mining. - Rina Singh; Jeffrey A. Graves; Douglas A. Talbert; William Eberle (MLDM (1), 2018)

Credit Default Mining Using Combined Machine Learning and Heuristic Approach. - Sheikh Rabiul Islam; William Eberle; Sheikh Khaled Ghafoor (CoRR, 2018)

Personalized news recommendation using graph-based approach. - Lenin Mookiah; William Eberle; Maitrayi Mondal (Intell. Data Anal., 2018)

A novel classifier ensemble approach for financial distress prediction. - Deron Liang; Chih-Fong Tsai; An-Jie Dai; William Eberle (Knowl. Inf. Syst., 2018)

Detecting DoS Attack in Smart Home IoT Devices Using a Graph-Based Approach. - Ramesh Paudel; Timothy Muncy; William Eberle (IEEE BigData, 2019)

Gene Selection and Clustering of Breast Cancer Data. - Farzana Ahamed Bhuiyan; Md Bulbul Sharif; Paul Joshua Tinker; William Eberle; Douglas A. Talbert; Sheikh Khaled Ghafoor; Lewis J. Frey (FLAIRS, 2019)

Detecting the Onset of a Network Layer DoS Attack with a Graph-Based Approach. - Ramesh Paudel; Peter Harlan; William Eberle (FLAIRS, 2019)

Discovering Suspicious Patterns Using a Graph Based Approach. - Sirisha Velampalli; Lenin Mookiah; William Eberle (FLAIRS, 2019)

Infusing domain knowledge in AI-based "black box" models for better explainability with application in bankruptcy prediction. - Sheikh Rabiul Islam; William Eberle; Sid C. Bundy; Sheikh Khaled Ghafoor (CoRR, 2019)

Investigating bankruptcy prediction models in the presence of extreme class imbalance and multiple stages of economy. - Sheikh Rabiul Islam; William Eberle; Sheikh K. Ghafoor; Sid C. Bundy; Douglas A. Talbert; Ambareen Siraj (CoRR, 2019)

Domain Knowledge Aided Explainable Artificial Intelligence for Intrusion Detection and Response. - Sheikh Rabiul Islam; William Eberle; Sheikh K. Ghafoor; Ambareen Siraj; Mike Rogers (AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (1), 2020)

Graph Filtering to Remove the "Middle Ground" for Anomaly Detection. - William Eberle; Lawrence Holder (IEEE BigData, 2020)

Towards Quantification of Explainability in Explainable Artificial Intelligence Methods. - Sheikh Rabiul Islam; William Eberle; Sheikh K. Ghafoor (FLAIRS, 2020)

Node Similarity For Anomaly Detection in Attributed Graphs. - Prajjwal Kandel; William Eberle (FLAIRS, 2020)

An Approach For Concept Drift Detection in a Graph Stream Using Discriminative Subgraphs. - Ramesh Paudel; William Eberle (ACM Trans. Knowl. Discov. Data, 2020)

Implications of Combining Domain Knowledge in Explainable Artificial Intelligence. - Sheikh Rabiul Islam; William Eberle (AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering, 2021)

Anomaly Detection in Edge Streams Using Term Frequency-Inverse Graph Frequency (TF-IGF) Concept. - Prabin B. Lamichhane; William Eberle (IEEE BigData, 2021)

Visualization of Anomalies using Graph-Based Anomaly Detection. - Ramesh Paudel; Lauren Tharp; Dulce Kaiser; William Eberle; Gerald C. Gannod (FLAIRS, 2021)

Explainable Artificial Intelligence Approaches: A Survey. - Sheikh Rabiul Islam; William Eberle; Sheikh Khaled Ghafoor; Mohiuddin Ahmed (CoRR, 2021)

Discovering Breach Patterns on the Internet of Health Things: A Graph and Machine Learning Anomaly Analysis. - Prabin B. Lamichhane; Hannah Mannering; William Eberle (FLAIRS, 2022)

Self-Organizing Map-Based Graph Clustering and Visualization on Streaming Graphs. - Prabin B. Lamichhane; William Eberle (ICDM (Workshops), 2022)

Incorporating the Concepts of Fairness and Bias into an Undergraduate Computer Science Course to Promote Fair Automated Decision Systems. - Sheikh Rabiul Islam; Ingrid Russell; William Eberle; Darina Dicheva (SIGCSE (2), 2022)

Instilling conscience about bias and fairness in automated decisions. - Sheikh Rabiul Islam; Ingrid Russell; William Eberle; Darina Dicheva (J. Comput. Sci. Coll., 2022)

Innovative Practice: Agile Training for Year-Long Capstone Project. - William Eberle; Gerald C. Gannod; Eric Brown (FIE, 2024)

Mode Collapse Detection Strategies in Generative Adversarial Networks for Credit Card Fraud Detection. - Farhat Lamia Barsha; William Eberle (FLAIRS, 2024)

Dynamic PageRank with Decay: A Modified Approach for Node Anomaly Detection in Evolving Graph Streams. - Ocheme Anthony Ekle; William Eberle (FLAIRS, 2024)

Anomaly Detection in Graph Structured Data: A Survey. - Prabin B. Lamichhane; William Eberle (CoRR, 2024)

Advances in Explainable, Fair, and Trustworthy AI. - Sheikh Rabiul Islam; Ingrid Russell; William Eberle; Douglas A. Talbert; Md Golam Moula Mehedi Hasan (Int. J. Artif. Intell. Tools, 2024)

Preface. - Ingrid Russell; Sheikh Rabiul Islam; William Eberle; Douglas A. Talbert; Md Golam Moula Mehedi Hasan (Int. J. Artif. Intell. Tools, 2024)

Anomaly Detection in Dynamic Graphs: A Comprehensive Survey. - Ocheme Anthony Ekle; William Eberle (ACM Trans. Knowl. Discov. Data, 2024)

An in-depth review and analysis of mode collapse in generative adversarial networks. - Farhat Lamia Barsha; William Eberle (Mach. Learn., 2025)