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Conference Paper
M. Georgiopoulos, Gelenbe, E., DeMara, R., Gonzalez, A., Mollaghasemi, M., Wu, A., Russell, I., Anagnostopoulos, G., and Secretan, J., “Assessing and Evaluating our progress on the CRCD Experiences at the University of Central Florida: An NSF Project”, in 2006 ASEE, Chicago, Illinois, 2006.
M. Georgiopoulos, Gelenbe, E., DeMara, R., Gonzalez, A., Mollaghasemi, M., Wu, A., Russell, I., Anagnostopoulos, G., and Secretan, J., “Assessing and Evaluating our progress on the CRCD Experiences at the University of Central Florida: An NSF Project”, 2006.
A. Koufakou, Wakchaure, A., Kursun, O., Georgiopoulos, M., Reynolds, K., and Eaglin, R., “Burglary data mining – A three tiered approach: Local satte and nation-wide”, in the 2nd Annual GIS Symposium at TU, Troy, Alabama, 2005.
K. Reynolds, Wakchaure, A., Kursun, O., Georgiopoulos, M., Reynolds, K., and Eaglin, R., “Burglary data mining – A three tiered approach: Local state and nation-wide”, in the 2nd Annual GIS Symposium at TU, Troy, Alabama, 2005.
K. Reynolds, Wakchaure, A., Kursun, O., Georgiopoulos, M., Reynolds, K., and Eaglin, R., “Burglary data mining – A three tiered approach: Local state and nation-wide”, in the 2nd Annual GIS Symposium at TU, Troy, Alabama, 2005.
I. Russel, Georgiopoulos, M., Castro, J., Neller, T., McCracken, D., and Bouvier, D., “Condensing the CC-2001 core in an Integrated Curriculum”, in CCSCNE (Consortium for Computing in Small Colleges in the Northeast), Providence, RI, 2003.
M. Georgiopoulos, Gelenbe, E., DeMara, R., Gonzalez, A., Kysilka, M., Mollaghasemi, M., Wu, A., Russell, I., Anagnostopoulos, G., and Secretan, J., “CRCD Experiences at the University of Central Florida: An NSF Project”, in the ASEE 2005 Annual Conference and Exposition, Portland Oregon, 2005.
K. Reynolds, Kursun, O., Georgiopoulos, M., and Eaglin, R., “Development of an Artificial Intelligence Clustering Algorithm to Detect Auto Theft Recovery Patterns”, in GIS Symposium 2004, Troy, AL, 2004.
K. Reynolds, Kursun, O., Eaglin, R., Chen, B., and Georgiopoulos, M., “Development of an Artificial Intelligent System for detection and visualization of auto theft recovery patterns”, in Computational Intelligence Conference on Homeland Security and Public Safety (CIHSPS, 2005), Orlando, FL, 2005.
M. Zhong, Rosander, B., Georgiopoulos, M., Anagnostopoulos, G., Mollaghasemi, M., and Richie, S., “Experiments with Micro-ARTMAP: Effect of the Network Parameters on the Network Performance”, in 2005 Artificial Neural Networks in Engineerin, St. Louis, MI, 2005.
M. Zhong, Rosander, B., Georgiopoulos, M., Anagnostopoulos, G., Mollaghasemi, M., and Richie, S., “Experiments with Micro-ARTMAP: Effect of the Network Parameters on the Network Performance”, in 2005 Artificial Neural Networks in Engineerin, St. Louis, MI, 2005.
M. Zhong, Rosander, B., Georgiopoulos, M., Anagnostopoulos, G., Mollaghasemi, M., and Richie, S., “Experiments with Safe Micro-ARTMAP: Effect of the Network Parameters on the Network Performance”, in WCCI 2006, Vancouver, Canada, 2006.
M. Zhong, Rosander, B., Georgiopoulos, M., Anagnostopoulos, G., Mollaghasemi, M., and Richie, S., “Experiments with Safe Micro-ARTMAP: Effect of the Network Parameters on the Network Performance”, in WCCI 2006, Vancouver, Canada, 2006.
M. Zhong, Coggeshall, D., Ghaneie, E. G., Pope, T., Rivera, M. A., Georgiopoulos, M., and Anagnostopoulos, G. C., “Gap-Based Estimation: Choosing the smoothing parameters for Probabilistic and General Regression Neural Networks”, in WCCI 2006, Vancouver, Canada, 2006.
G. L. Heileman, Georgiopoulos, M., and Roome, W. D., “A general framework for concurrent simulation on neural network models”, in International Joint Conference on Neural Networks (IJCNN), Baltimore, MD, 1992.
J. Reeder, Georgiopoulos, M., Castro, J., Burns, S., Anagnostopoulos, G., and Mollaghasemi, M., “Hilbert Space Filling Curve Nearest Neighbor”, in The ISAS and CITSA 2005, Orlando, FL, 2005.
J. Secretan, Castro, J., Chadha, A., Huber, B., Tapia, J., Georgiopoulos, M., Anagnostopoulos, G., and Richie, S., “Pipelining of ART architectures (FAM, EAM, GAM) without match-tracking (MT)”, in 2005 Artificial Neural Networks in Engineering, St. Louis, MI, 2005.
G. C. Anagnostopoulos, Georgiopoulos, M., Ports, K., Richie, S., Cardinale, N., White, M., Kepuska, V., Chan, P. K., Wu, A., and Kysilka, M., “Project EMD-MLR: Educational Materials Development and Research in Machine Learning for Undergraduate students”, in 2006 ASEE, Chicago, Illinois, 2006.
G. C. Anagnostopoulos, Georgiopoulos, M., Ports, K., Richie, S., Cardinale, N., White, M., Kepuska, V., Chan, P. K., Wu, A., and Kysilka, M., “Project EMD-MLR: Educational Materials Development and Research in Machine Learning for Undergraduate students”, in the ASEE 2005 Annual Conference and Exposition, Portland, Oregon, 2005.
A. Koufakou, Ortiz, E., Georgiopoulos, M., Anagnostopoulos, G. C., and Reynolds, M. K., “A scalable and efficient otlier detection strategy for categorical data”, in Annual IEE International Conference on Tools with Artificial Intelligence, 2007 (ICTAI 2007),, Patras, Greece, 2007.
Journal Article
O. Kursun, Koufakou, A., Wakchaure, A., Georgiopoulos, M., Reynolds, K., and Eaglin, R., “Answer: approximate Name Search with Errors in Large Databases by a Novel Approach Based on Prefix-dictionary”, International Journal on Artificial Intelligence Tools, vol. 15.5, pp. 839–848, 2006.
F. Miwakeichi, Ramirez-Padron, R., and P. Valdes-Sosa, O. T., “A comparison of Non-linear Non-parametric Models for Epilepsy Data”, Computers in Biology and Medicine, vol. 31.1, pp. 41–57, 2001.
M. Georgiopoulos, Russell, I., Castro, J., Wu, A., Kysilka, M., and DeMara, R., “A CRCD Experience: Integrating machine learning modules into introductory engineering and science programming courses”, Proceedings of the 2003 American Society for Engineering Education Annual Conference & Exposition, 2003.
O. Kursun, Koufakou, A., Chen, B., Georgiopoulos, M., Reynolds, K., and Eaglin, R., “A Dictionary-Based Approach to Fast and Accurate Name Matching in Large Law Enforcement Databases”, IEEE Intelligence and Security Informatics (ISI) Conference, pp. 72–82, 2006.
M. Zhong, Rosander, B., Georgiopoulos, M., Anagnostopoulos, G. C., Mollaghasemi, M., and Richie, S., “Experiments with Safe ARTMAP and Comparisons to Other ART Networks”, Proceedings of the 2006 IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN 2006), pp. 720–727, 2006.
M. Zhong, Rosander, B., Georgiopoulos, M., Anagnostopoulos, G. C., Mollaghasemi, M., and Richie, S., “Experiments with Safe ARTMAP and Comparisons to Other ART Networks”, Proceedings of the 2006 IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN 2006), pp. 720–727, 2006.
M. Zhong, Rosander, B., Georgiopoulos, M., Anagnostopoulos, G. C., Mollaghasemi, M., and Richie, S., “Experiments with Safe micro-ARTMAP: Effect of the Network Parameters on the Network Performance”, Neural Networks, vol. 20.2, pp. 245–259, 2007.
M. Zhong, Rosander, B., Georgiopoulos, M., Anagnostopoulos, G. C., Mollaghasemi, M., and Richie, S., “Experiments with Safe micro-ARTMAP: Effect of the Network Parameters on the Network Performance”, Neural Networks, vol. 20.2, pp. 245–259, 2007.
A. Koufakou, Secretan, J., Reeder, J., Cardona, K., and Georgiopoulos, M., “Fast Parallel Outlier Detection for Categorical Datasets using MapReduce”, IEEE World Congress on Computational Intelligence (WCCI), 2008.
D. Charalampidis, Kasparis, T., Georgiopoulos, M., and Rolland, J., “A Fuzzy ARTMAP based classification of natural textures”, Proceedings of the 18th International Conference of the North American Fuzzy Information Processing Society, pp. 507–511, 1999.
M. Zhong, Coggeshall, D., Georgiopoulos, M., Anagnostopoulos, G. C., Mollaghasemi, M., and Richie, S., “Gap-Based Estimation: Choosing the Smoothing Parameters for Probabilistic and General Regression Neural Networks”, Proceedings of the 2006 IEEE-INNS-ENNS International Joint Conference on Neural Networks, pp. 1870–1877, 2006.
G. L. Heileman, Georgiopoulos, M., and Roome, W. D., “A general framework for concurrent simulation on neural network models”, IEEE Transactions on Software Engineering, vol. 18, pp. 551-562, 1992.
J. Reeder and Georgiopoulos, M., “Generative Neural Networks for Multi-Task Life-Long Learning”, The Computer Journal, vol. 57, no. 3, pp. 427-450, 2014.
G. Rabadi, Anagnostopoulos, G. C., and Mollaghasemi, M., “A heuristic algorithm for the just-in-time single machine scheduling problem with setups: A comparison with simulated annealing”, vol. 32, pp. 326–335, 2007.
C. Young, Georgiopoulos, M., Hagen, S., Geiger, C., Dagley-Falls, M., Islas, A., Ramsey, P., Lancey, P., Forde, D., and Bradbury, E., “Improving Student Learning in Calculus through Applications”, International Journal of Mathematical Education in Science and Technology, vol. 42, pp. 591-604, 2011.
J. Reeder, Gita, S., Georgiopoulos, M., and Anagnostopoulos, G. C., “Intelligent Trading Agents for Massively Multi-player Game Economies”, Proceedings of the Fourth Artificial Intelligence and Interactive Digital Entertainment Conference, pp. 102–107, 2008.
J. Reeder, Miguez, R., Sparks, J., Georgiopoulos, M., and Anagnostopoulos, G. C., “Interactively Evolved Modular Neural Networks for Game Agent Control”, IEEE Symposium on Computational Intelligence and Games (CIG 08, pp. 167–174, 2008.
X. Rui, Anagnostopoulos, G. C., and II, W. D., “Multiclass Cancer Classification Using Semisupervised Ellipsoid ARTMAP and Particle Swarm Optimization with Gene Expression Data”, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 4., pp. 65–77, 2007.
A. Koufakou, Ortiz, E., Georgiopoulos, M., Anagnostopoulos, G. C., and Reynolds, K., “A Scalable and Efficient Outlier Detection Strategy for Categorical Data”, International Conference on Tools with Artificial Intelligence (ICTAI), 2007.
T. Kasparis, Charalampidis, D., Georgiopoulos, M., and Rolland, J. P., “Segmentation of textured images based on fractals and image filtering”, Pattern Recognition, vol. 34.10, pp. 1963–1973, 2001.
T. Kasparis, Charalampidis, D., Georgiopoulos, M., and Rolland, J. P., “Segmentation of textured images based on fractals and image filtering”, Pattern Recognition, vol. 34.10, pp. 1963–1978, 2001.
R. Ramirez-Padron, Foregger, D., Manuel, J., Georgiopoulos, M., and Mederos, B., “Similarity Kernels for Nearest Neighbor-based Outlier Detection”, Lecture Notes in Computer Science, vol. 6065/2010, pp. 159-170, 2010.
R. C. Watkins, Reynolds, K. M., DeMara, R., Georgiopoulos, M., Gonzalez, A., and Eaglin, R., “TRACKING DIRTY PROCEEDS: EXPLORING DATA MINING TECHNOLOGIES AS TOOLS TO INVESTIGATE MONEY LAUNDERING”, Police Practice and Research, vol. 4.2, pp. 163–178, 2003.