Action Rules

    Conference

  • Wyatt Green, Tom Johnsten, and Ryan G. Benton, "TADS: Transformation of Anomalies in Data Streams", Discriminative Pattern Mining Workshop at IEEE International Conference on Big Data, pp. 4284-4292, Dec 10 - 13, 2020.
  • Tom Johnsten, Wyatt Green, Lowell Crook, Ho Yin Chan, Ryan Benton and David Bourrie, "Discovery of Action Rules for Continuously Valued Data", IEEE International Conference on Cognitive Machine Intelligence, pp. 127-135, December 12-14, 2019.
  • Grant Daly, Ryan Benton, and Tom Johnsten, "A Multi-Objective Evolutionary Action Rule Mining Method", in IEEE Congress on Evolutionary Computation, pp. 2105-2112, July 8 - 13, 2018.
  • Tom Johnsten, Samy Alihamad, Ashwin Kannalath, and Ryan G Benton "Targeted Action Rule Discovery", in International Conference on Machine Learning and Applications, Miami, Florida, pp. 348-353, December 4-7, 2013.

    • Workshop

  • Blake Johns, Ryan Benton, Tom Johnsten and David Bourrie, "RARE: Rare Action Rule Exploration", 2nd Discriminative Pattern Mining Workshop at IEEE International Conference on Big Data, pp. 2603-2610, Dec 15 - 18, 2021.
  • Djellel Difallah, Ryan Benton, Tom Johnsten and Vijay Raghavan, "FAARM: Frequent Association Action Rules Mining Using FP-Tree", in Workshop on Domain Driven Data Mining, part of 11th IEEE International Conference on Data Mining Workshops, Vancouver, Canada, pp. 398-404, December 11, 2011.

Alzheimer's Disease Prediction

    Journal

  • Murat Seckin Ayhan, Ryan G. Benton, Vijay V. Raghavan, and Suresh Choubey, "Exploitation of 3D Stereotactic Surface Projection for Predictive Modeling of Alzheimer's Disease", in International Journal of Data Mining and Bioinformatics, Vol. 7, No 2, pp. 146-165, 2013.

    • Conference

  • Ryan G. Benton, Suresh Choubey, David G. Clark, Tom Johnsten, and Vijay V. Raghavan, "Diagnosis and Grading of Alzheimer's Disease via Automatic Classification of FDG-PET Scans", in International Conference on Brain and Health Informatics, Maebashi, Japan, pp. 266-276, October 29-31, 2013.
  • Murat Seckin Ayhan, Ryan G. Benton, Vijay V. Raghavan, and Suresh Choubey, "Composite Kernels for Automatic Relevance Determination in Computerized Diagnosis of Alzheimer's Disease", in International Conference on Brain and Health Informatics, Maebashi, Japan, pp. 126-137, October 29-31, 2013.
  • Murat Seckin Ayhan, Ryan G. Benton, Vijay V. Raghavan, and Suresh Choubey, "Exploitation of 3D Stereotactic Surface Projection for Automated Classification of Alzheimer's Disease According to Dementia Levels", in IEEE International Conference on Bioinformatics and Biomedicine, Hong Kong, pp. 516-519, December 18-21, 2010.
  • Blake Lemoine, Sara Rayburn, Ryan Benton and ADNI, "Data Fusion and Feature Selection for Alzheimer's Diagnosis", in International Conference on Brain Informatics, Toronto, Canada, pp. 320-327, August 28-30, 2010.

    • Workshop

  • Murat Seckin Ayhan, Ryan Benton, Vijay V. Raghavan, and Suresh Choubey, "Utilization of Domain-Knowledge for Simplicity and Comprehensibility in Predictive Modeling of Alzheimer's Disease", in International Workshop on Multiscale Biomedical Imaging Analysis, held in conjunction with IEEE International Conference on Bioinformatics and Biomedicine, Philadelphia, Pennsylvania, pp. 265-272, October 4-7, 2012.

    • Abstract

  • Murat Seckin Ayhan, Ryan Benton, Vijay V. Raghavan, and Suresh Choubey, "Determining Relevant Features Based on 3D Stereotactic Surface Projection to Detect Dementia Caused by Alzheimer's Disease", in 7th Annual Biotechnology and Bioinformatics Symposium, Lafayette, Louisiana, pp. 91-92, October 14-15, 2010.

CyberSecurity/Digital Forensics

    Journal

  • Dustin M. Mink, Jeffrey McDonald, Sikha Bagui, William B. Glisson, Jordan Shropshire, Ryan Benton, and Samuel Russ, "Near-Real-Time IDS for the U.S. FAA’s NextGen ADS-B", Big Data and Cognitive Computing, Vol 5, No 2, 15 pages, 2021.
  • Patrick Luckett, Jeffrey Todd McDonald, William Bradley Glisson, Ryan Benton, Joel Dawson, and Blair A. Doyle, "Identifying Stealth Malware Using CPU Power Consumption and Learning Algorithms", in Journal of Computer Security, Vol. 26, No. 5, pp 589-613, 2018.

    • Conference

  • Dhanasak Bhumchai and Ryan Benton, "Detection of Ethereum Eclipse Attack Based on Hybrid Method and Dynamic Weighted Entropy", IEEE SouthEastCon, 8 pages, Apr 13-16, 2023.
  • Dhanasak Bhumchai and Ryan Benton, "Feature Extraction of Network Traffic in Ethereum Blockchain Network Layer for Eclipse Attack Detection", IEEE SouthEastCon, 8 pages, Apr 13-16, 2023.
  • Reeve Cabral, J. Todd McDonald, Lee M. Hively, and Ryan G. Benton, "Profiling CPU Behavior for Detection of Android Ransomwares", IEEE SouthEastCon, pp. 690-697, Apr 13 - 16, 2022.
  • Matthew Peterson, Todd Andel, and Ryan Benton, “Towards Detection of Selfish Mining Using Machine Learning”, International Conference on Cyber Warfare and Security, pp. 237-243, Mar 17 – 18, 2022.
  • Jordan Shropshire and Ryan Benton, "The Future Role of Artificial Intelligence in Systems Hardening", Southeastern Decision Sciences Institute Annual Meeting, pp. 253-261, Feb 16-18, 2022.
  • Joshua Hightower, William Bradley Glisson, Ryan Benton and J. Todd McDonald, "Classifying Android Applications Via System Stats", IEEE International Conference on Big Data, pp. 5388-5394, Dec 15 - 18, 2021.
  • Jordan Shropshire, Madelyn Allen, and Ryan Benton, "Taxonomy of Applications of Artificial Intelligence for Cyber Security Administration", Annual Symposium on Information Assurance, pp. 73-80, June 8-9, 2021
  • Alberto Alejandro Ceballos Delgado, William Bredley Glisson, Narasimha Shashidhar, J. Todd McDonald, George Grispos, and Ryan Benton, "Detecting Deception Using Machine Learning", Hawaii International Conference on System Sciences, pp. 7122-7131, Jan 5-8, 2021
  • Thomas Watts, Ryan Benton, David Bourrie, and Jordan Shropshire, "Insight from a Containerized Kubernetes Workload Introspection", Hawaii International Conference on System Sciences, pp. 6955-6964, Jan 5-8, 2021
  • J. Todd McDonald, Nathan Herron, William Brad Glisson, and Ryan Benton, "Machine Learning-Based Android Malware Detection Using Manifest Permissions", Hawaii International Conference on System Sciences, pp. 6976-6985, Jan 5-8, 2021
  • Jordan Shropshire and Ryan Benton, "User Evaluation of a Visual Approach to Cloud Security", Southeast Decision Sciences Institute Annual Meeting, 11 pages, Feb 12-14, 2020.
  • Jordan Shropshire and Ryan Benton, "Container and VM Visualization for Rapid Forensic Analysis", Hawaii International Conference on System Sciences, pp. 6397-6406, Jan 6-10, 2020.
  • Avinash Kumar, William Bradley Glisson,and Ryan Benton, "Network Attack Detection using an Unsupervised Machine Learning Algorithm", Hawaii International Conference on System Sciences, pp. 6496-6505, Jan 6-10, 2020.
  • Thomas Watts, Ryan G. Benton, William Bradley Glisson, and Jordan Shropshire, "Insight from a Docker Container Introspection", Hawaii International Conferenc on System Sciences, pp 7194-7203, Jan 8 - 11, 2019.

    • Workshop

  • Edward Harshany, Ryan Benton, David Bourrie, Michael Black, and William Glisson, "DFS3: Automated Distributed File System Storage State Reconstruction", International Workshop on Digital Forensics at the International Conference on Availability, Reliability and Security, 10 pages, August 25-28, 2020.
  • Adam M. Gautier, Todd R. Andel, and Ryan Benton, "On-Device Detection via Anomalous Environmental Factors", Software Security, Protection and Reverse Engineering Workshop, 5 pages, December 3-4, 2018.

    • Abstract

  • Edward Harshany, Ryan Benton, David Bourrie, and William Glisson, "Big Data Forensics: Hadoop 3.2.0 Reconstruction", Digital Forensics Research Workshop EU, 2 pages, June 3-5, 2020.

Health

    Book Chapters

  • Ryan Benton,"Effective Removal of Noisy Data via Batch Effect Processing", in Bioinformatics in microRNA Research, Jingshuan Huang, Glen M. Borchert, Dejing Dou, Jun (Luke) Huan, Wejun Lan, Ming Tan, and Bin Wu (ed.), Springer, 187-106, 2017.
  • Sumi Singh, Ryan Benton, Anurag Singh, and Ashunman Singh,"Machine Learning Techniques in Exploring micro-RNA Gene Discovery, Targets, and Functions", in Bioinformatics in microRNA Research, Jingshuan Huang, Glen M. Borchert, Dejing Dou, Jun (Luke) Huan, Wejun Lan, Ming Tan, and Bin Wu (ed.), Springer, 211-224, 2017.

    • Journals

  • Aleise McGowan, Scott Sittig, David Bourrie, Ryan Benton, and Sriram Iyengar, "The Intersection Of Persuasive System Design and Personalization: Evaluating the Persuasiveness of Mobile Health", JMIR mHealth and uHealth, Vol 10, No 9, 23 pages, 2022
  • Raymond J. Langley, Marie E. Migaud, Lori Flores, J. Will Thompson, Elizabeth A. Kean, Murphy M. Mostellar, Matthew Mowry, Patrick Luckett, Lina D. Purcell, James Lovato, Sheetal Gandotra, Ryan Benton, D. Clark Files, Kevin S. Harrod, Mark N. Gillespie and Peter E. Morris, "A metabolomic endotype of bioenergetic dysfunction predicts mortality in critically ill patients with acute respiratory failure", Scientific Reports, Vol 11, 12 pages, 2021.
  • Fangwan Huang, Xiuyu Leng, Mohan Vamsi Kasukurthi, Yulong Huang, Dongqi Li, Shaobo Tan, Guiying Lu, Juhong Lu, Ryan G. Benton, Glen M. Borchert, and Jingshan Huang, "Utilizing Machine Learning Techniques to Predict the Efficacy of Aerobic Exercise Intervention on Young Hypertensive Patients Based on Cardiopulmonary Exercise Testing", Journal of Healthcare Engineering, Vol 2021, 14 pages, 2021.
  • Bin Ma, Zhaolong Wu, Shengyu Li, Ryan Benton, Dongqi Li, Yulong Huang, Mohan Vamsi Kasukurthi, Jingwei Lin, Glen M. Borchert, Shaobo Tan, Gang Li, Meihong Yang and Jingshan Huang, "Development of a support vector machine learning and smart phone Internet of Things-based architecture for real-time sleep apnea diagnosis", BMC Medical Informatics and Decision Making, Vol 20, Supplement 14, 13 pages, 2020.
  • Jian Li, Zelin Zhang, Shengyu Li, Ryan Benton, Yulong Huang, Mohan Vamsi Kasukurthi, Dongqi Li, Jingwei Lin, Glen M. Borchert, Shaobo Tan, Gang Li, Bin Ma, Meihong Yang and Jingshan Huang, "A partial encryption algorithm for medical images based on quick response code and reversible data hiding technology", BMC Medical Informatics and Decision Making, Vol 20, Supplement 14, 16 pages, 2020.
  • Robinette Renner, Shengyu Li, Yulong Huang, Ada Chaeli van der Zijp-Tan, Shaobo Tan, Dongqi Li, Mohan Vamsi Kasukurthi, Ryan Benton, Glen M. Borchert, Jingshan Huang and Guoqian Jiang, "Using an artificial neural network to map cancer common data elements to the biomedical research integrated domain group model in a semi-automated manner", BMC Medical Informatics and Decision Making, Vol. 19, Supplement 7, 13 pages, 2019.
  • Bin Ma, Chunxiao Li, Zhaolong Wu, Yulong Huang, Ada Chaeli van der Zijp-Tan, Shaobo Tan, Dongqi Li, Ada Fong, Chandan Basetty, Glen M. Borchert, Ryan Benton, Bin Wu and Jingshan Huang,"Muscle fatigue detection and treatment system driven by internet of things", BMC Medical Informatics and Decision Making, Vol. 19, Supplement 7, 9 pages, 2019.

    • Conference

  • Maureen Van Devender, William Glisson, Ryan Benton, and George Grispos, "Understanding De-identification of Healthcare Big Data", Americas Conference on Information Systems, 10 pages, August 10-12, 2017.
  • Satya Katragadda, Harika Karnati, Murali Pusala, Vijay Raghavan, and Ryan Benton, "Detecting Adverse Drug Effects Using Link Classification on Twitter Data", in IEEE International Conference on Bioinformatics and Biomedicine, Bethesda, Maryland, pp. 675-679, November 9-12, 2015.
  • Sonya Hsu, Ryan Benton, and Raju Gottumukkala, "Real-Time Flu Monitoring System and Decision Informatics", in Hawaii International Conference on System Sciences, Kauai, Hawaii, pp. 2794-2803, January 5-8, 2015.

    • Workshop

  • Guanyi Yang, Xiuyu Leng, Fangwan Huang, Mohan Vamsi Kasukurthi, Yulong Huang, Dongqi Li, Jingwei Lin, Shaobo Tan, Guiying Lu, Ryan Benton, Glen M. Borchert, Bin Ma, and Jingshan Huang, "Use CPET data to predict the intervention effect of aerobic exercise on young hypertensive patients", Biomedical and Health Informatics at IEEE International Conference on Bioinformatics and Biomedicine, pp. pp. 1699-1702, Nov 18-21, 2019.
  • Mohan Vamsi Kasukurthi, Dihua Zhang, Mika Housevera, Yulong Huang, Dongqi Li, Jingwei Lin, Shaobo Tan, Bin Ma, Ryan Benton, Shengyu Li, Glen M. Borchert, and Jingshan Huang, "SURFr: Algorithm for identification and analysis of ncRNA-derived RNAs", Biomedical and Health Informatics at IEEE International Conference on Bioinformatics and Biomedicine, pp. 1504-1507, Nov 18-21, 2019.
  • Jian Li, Zelin Zhang, Shengyu Li, Ryan Benton, Yulong Huang, Mohan Vamsi Kasukurthi, Dongqi Li, Jingwei Lin, Glen M. Borchert, Shaobo Tan, Bin Ma, Meihong Yang, and Jingshan Huang, "Reversible Data Hiding Based Key Region Protection Method in Medical Images", Biomedical and Health Informatics at IEEE International Conference on Bioinformatics and Biomedicine, pp. 1526-1530, Nov 18-21, 2019.
  • Bin Ma, Zhaolong Wu, Shengyu Li, Ryan Benton, Dongqi Li, Yulong Huang, Mohan Vamsi Kasukurthi, Jingwei Lin, Glen M. Borchert, Shaobo Tan, Meihong Yang, and Jingshan Huang, "A SVM-Based Algorithm to Diagnose Sleep Apnea", Biomedical and Health Informatics at IEEE International Conference on Bioinformatics and Biomedicine, pp. 1556-1560, Nov 18-21, 2019.
  • Robinette Renner, Shengyu Li, Yulong Huang, Shaobo Tan, Dongqi Li, Ada chaeli van der Zijp-Tan, Ryan Benton, Glen M. Borchert, Jingshan Huang, and Guoqian Jiang, "Mapping Common Data Elements to a Domain Model Using an Artificial Neural Netowrk", International Workshop on Biomedical and Health Informatics at IEEE International Conference on Bioinformatics and Biomedicine, pp 1532-1535, December 3-6, 2018

    • Abstract

  • Mark N. Gillespie, Viktor M. Pastukh, Raymond J. Langley, David Roveda, Valeria King, Justin Roberts, Tom Johnsten, Ryan Benton, Grant Daly, Bin Wang, Daniel Vera, and Hank Bass, "Mutational Artifacts Are Introduced in DNA Regulatory Regions by Oxidative Base Damage Associated with Hypoxic Signaling: Implications for Accurate Identification of Sequence Variants", presented in American Thoracic Society 2017 International Conference, Washington D.C., May 14-15, 2017 and published in American Journal of Respiratory and Critical Care Medicine, Vol 195, No. A75, A2493.

Image Processing/Mining

    Book Chapter

  • Biren Shah, Ryan Benton, Zonghuan Wu and Vijay Raghavan, "Automatic and Semi-automatic Techniques for Image Annotation", in Semantic-Based Visual Information Retrieval, Yu-Jin Zhang(ed.), Idea Group Publishing, pp. 112-134, 2007.

    • Conference

  • Patrick Luckett, Thomas Watts, Jeffery T. McDonald, Lee Hively, and Ryan Benton, "A Deep Learning Approach to Phase-Space Analysis for Seizure Detection", ACM Internation Conference on Bioinformatics, Computational Biology and Health Informatics, pp. 190-196, September 7-10, 2019.
  • C Scott Brown, William Bradley Glisson, Ryan Benton, Jordan Shropshire, Thomas Watts, and Timothy Sullivan, "Image Segmentation Stability: An Empirical Investigation", IEEE SoutheastCon, 8 pages, April 19-22, 2018.
  • Ryan G. Benton and Chee-Hung Henry Chu, "Camera Pose Estimation by an Artificial Neural Network", Proceedings of the 2006 International Conference on Neural Information Processing, Hong Kong, pp. 604-611, October 3-6, 2006.
  • Ryan Benton and Chee-Hung Henry Chu, "Soft Computing Approach to Steganalysis of Digital Images", IEEE International Conference on Information Technology: Research and Education, Hsinchu, Taiwan, pp. 105-109, June 27-30, 2005.

Local Models


    Conference

  • CScott Brown and Ryan Benton, "Decision Surfaces of Localized Classifiers", International Joint Conference on Neural Networks, 8 pages, July 19-24, 2020
  • CScott Brown and Ryan Benton, "Local Gaussian Process Features for Clinical Sensor Time-Series", Machine Learning and Artificial Intelligence in Bioinformatics and Medical Informatics at IEEE International Conference on Bioinformatics and Biomedicine, pp. 1288-1295, Nov 18-21, 2019.

Predictive Maintenance


    Journal

  • Suresh Choubey, Ryan G. Benton, and Tom Johnsten, A Holistic End-to-End Prescriptive Maintenance Framework Data-Enabled Discovery and Applications, Vol 4, 20 pages, 2020.

    • Workshop

  • Suresh Choubey, Ryan Benton, and Tom Johnsten, "Dynamic Thresholding Leading to Optimal Inventory Maintenance", Second Workshop on Big Data Predictive Maintenance Using Artificial Intelligence (BDPM-AI) at IEEE International Conference on Big Data, pp. 4112-4121, Dec 10 - 13, 2020.
  • Suresh Choubey, Ryan Benton, and Tom Johnsten, "Prescriptive Equipment Maintenance: A Framework", Big Data Predictive Maintenance using Artificial Intelligence at IEEE International Conference on Big Data, pp. 4366-4374, Dec 6-12, 2019.

Sequence Representation

    Book Chapter

  • Ying Xie, Tom Johnsten, Vijay V. Raghavan, Ryan G. Benton, and William Bush, “A Comprehensive Granular Model for Decision Making with Complex Data” in Granular Computing and Decision-Making: Interactive and Iterative Approaches, Witold Pedrycz and Shyi-Ming Chen (ed.), Springer, pp. 33-46, 2015.

    • Journal

  • Tom Johnsten, Laura Fain, Leanna Fain, Ryan Benton, Ethan Butler, Lewis Pannell, and Ming Tan, "Exploiting Multi-Layered Vector Spaces for Signal Peptide Detection", International Journal of Data Mining and Bioinformatics, Vol. 13, No. 2, pp 141-157, 2015.

    • Invited

  • Vijay V. Raghavan, Ryan G. Benton, Tom Johnston, and Ying Xie, "Representations for Large-scale Sequence Data Mining: A Tale of Two Vector Space Models", in International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, pp. 15-25, Halifax, Nova Scotia, Canada, October 11-14, 2013.

    • Conference

  • Tom Johnsten, Aishwarya Prakash, Grant T. Daly, Ryan G. Benton, and Tristan Clark, "Computational Framework for Generating Synthetic Signal Peptides", ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, 7 pages, Aug 7-10, 2022.
  • Colby Parker, J. Todd McDonald, Tom Johnsten, and Ryan Benton, "Android Malware Detection Using Step-Size Based Multi-layered Vector Space Models", IEEE International Conference on Malicious and Unwanted Software, 10 pages, October 22-24, 2018.
  • Can Akkoç, Tom Johnsten and Ryan Benton, "Multi-layered Vector Spaces for Classifying and Analyzing Biological Sequences", in International Conference on Bioinformatics and Computational Biology, New Orleans, pp. 160-166, March 23-25, 2011.

Social Meda Event Detection

    Conference

  • Satya Katragadda, Ryan Benton, and Vijay Raghavan, "Sub-Event Detection from Tweets", The International Joint Conference on Neural Networks, pp. 2128-2135, May 14-19, 2017.
  • Satya Katragadda, Ryan Benton, and Vijay Raghavan, "Framework for Real-Time Event Detection using Multiple Social Media Sources", 50th Annual Hawaii International Conference on System Sciences, pp. 1716-1725, January 3-7, 2017.
  • Satya Katragadda, Ryan Benton, Shahid Virani, and Vijay Raghavan, "Detection of Event Onset using Twitter", in IEEE International Joint Conference on Neural Networks, Vancouver, Canada, pp. 1539-1546, July 24-29, 2016.

Targeted Association Mining

    Conference

  • Jay Lewis, Ryan Benton, David Bourrie, and Jennifer Lavergne, "Enhancing Itemset Tree Rules and Performance", IEEE International Conference on Big Data, pp. 1143-1150, Dec 6-12, 2019.
  • Jennifer Lavergne, Ryan Benton, Vijay Raghavan and Alaaeldin Hafez, "DynTARM: An In-Memory Data Structure for Targeted Strong and Rare Association Rule Mining Over Time-Varying Domains", in IEEE/WIC/ACM International Conference on Web Intelligence, Atlanta, GA, pp. 298-306, October 29-31, 2013.
  • Jennifer Lavergne, Ryan Benton, and Vijay V. Raghavan, "TRARM-RelSup: Targeted Rare Association Rule Mining Using Itemset Trees and the Relative Support Measure", in 20th International Symposium on Methodologies for Intelligent Systems, Macau, pp. 61-70, December 4-7, 2012.
  • Jennifer Lavergne, Ryan Benton, and Vijay V. Raghavan, "Min-Max Itemset Trees for Dense and Categorical Datasets", in 20th International Symposium on Methodologies for Intelligent Systems, Macau, pp 51-60, December 4-7, 2012.

Wireless

    Journal

  • Gui-Liang Feng, Itthichok Jangjaimon, and Ryan Benton, "Fast Wireless Network Coding for Real-Time Data", in Communications in Information Science and Management Engineering, http://www.jcisme.org/paperInfo.aspx?ID=13475, Vol. 2, No. 12, pp. 71-85, Dec. 2012

    • Conference

  • Gui-Liang Feng, Itthichok Jangjaimon and Ryan Benton, "A Class of Wireless Network Coding Schemes", in in IEEE International Conference on Electro/Information Technology, Mankato, Minnesota, 6 pages, May 15-17, 2011.

Other Topics

    Journal

  • Sukhwan Jung, Rachana Reddy Kandadi, Rituparna Datta, Ryan Benton, and Aviv Segev, Identification of Technology-relevant Entities Based on Trend Curves and Semantic Similarities, International Journal of Web and Semantic Technology, iVol 11, No. 1/2/3, pp 1-16, 2020

    • Special Report

  • Vijay Raghavan, Ying Xie, Tom Johnsten, Ryan Benton, Blake Lemoine, Djellel Difallah, "Concept Map-based Organized for REsearch Portfolios (C-MORE)", in CISE and SBE AC Subcomittee on Discovery in a Research Portfolio: Tools for Structuring, Analyzing, Visualizing and Interacting with Proposal and Award Portfolios, Nov. 2011.

    • Conference

  • Alec Austin and Ryan Benton, "Effects of Missing Members on Classifier Ensemble Accuracy", IEEE International Conference on Big Data, pp. 4998-5006, Dec 10 - 13, 2020.
  • Sukhwan Jung, Rachana Reddy Kandadi, Rituparna Datta, Ryan Benton and Aviv Segev, "Identification of Technology-Relevant Entities Based on Trend Curves", International Conference on Information Technology Convergence and ServicesVancouver, Canada, pp. 1-13, May 30-31, 2020.
  • Mores Prachyabrued, Timothy Roden, and Ryan G. Benton, "Procedural generation of stylized 2D maps", in Proceedings of the International Conference on Advances in Computer Entertainment Technology (ACE 2007), Salzburg, Austria, pp. 147-150, June 13-15, 2007.
  • Surendra Karnatapu, Karthik Ramachandran, Zonghuan Wu, Biren Shah, Vijay V. Raghavan and Ryan Benton, "Estimating Size of Search Engines in an Uncooperative Environment", Proceedings of the 2nd International Workshop on Web-based Support Systems, Beijing, China, pp. 81-87, September 20, 2004.
  • Ryan Benton, Miroslav Kubat, and Rasaiah Loganantharaj, "Meta-Classifiers and Selective Superiority", Proceedings of the 13th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, New Orleans, Louisiana, pp. 434-442, June 19-22, 2000.
  • Rasaiah Loganantharaj and Ryan Benton, "Automatic Discovery of Clusters", Proceedings of the ISCA 8th International Conference on Intelligent Systems, Denver, Colorado, pp. 45-48, June 24-26, 1999.
  • N. Pissinou, R. Benton, B. Bhagyavati, and S. Kurkovsky, "A Roadmap to the Utilization of Intelligent Information Agents: Are Intelligent Agents the link between the Database and Artificial Intelligence Communities?", Proceedings of the 1997 IEEE Knowledge & Data Engineering Exchange Workshop, Newport Beach, California, pp. 196-205, November 4, 1997.
  • Ryan Benton, Afshin Ganjoo, Beth Lumetta, Daryl Spillman, and Jason Ring, "Adaptive Wavelet Transforms of Singular and Chaotic Signals", Proceedings of the SPIE Wavelet Applications III, Orlando, Florida, pp. 136-143, April 8-12, 1996.
  • Ryan Benton, "Using Genetic Algorithms to Improve Interpretation of Satellite Data", Proceedings of the 33rd Annual ACM Southeast Conference, Clemson University, South Carolina, pp. 143-145, March 17-18, 1995.

    Workshop

  • Kolitha Warnakulasooriya, Ryan G. Benton, and Aviv Segev, "Priority Basis Task Allocation for Drone Swarms", Workshop on Multi-Agent Path Finding at AAAI, 8 pages, Feb 7-14, 2023.
  • Shaaban Abbady, Cheng-Yuan Ke, Jennifer Lavergne, Jian Chen, Vijay Raghavan and Ryan Benton, "Online Mining for Association Rules and Collective Anomalies in Data Streams", in the 2nd Workshop on Real-Time and Stream Processing In Big Data at the IEEE International Conference on Big Data, pp. 2288-2297, December 11, 2017.
  • Murali. K. Pusala, Ryan G. Benton, Vijay V. Raghavan, and Raju N. Gottumukkala, “Supervised Approach to Rank Predicted Links Using Interestingness Measures”, International Workshop on Biomedical and Health Informatics at IEEE International Conference on Bioinformatics and Biomedicine, pp. 1085 - 1092, November 13-16, 2017.
  • Dustin Mink, William B. Glisson, Ryan Benton, and Kim-Kwang Raymond Choo, "Manipulating the Five V’s in the Next Generation Air Transportation System", in 1st Workshop on Security and Privacy in the Internet of Things (SePrIoT) at the 13th International Conference on Security and Privacy in Communication Networks (SecureComm 2017), October 25, 2017.

    Abstracts

  • Aviv Segev, Rituparna Datta, Ryan Benton, and Dorothy Curtis, "OINNIONN - Outward Inward Neural Network and Inward Outward Neural Network Evolution", Genetic and Evolutionary Computation Conference Companion, pp. 79-80, July 13-17, 2019.
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