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Author Title Type [ Year(Desc)]
2007
M. Zhong, Georgiopoulos, M., and Anagnostopoulos, G. C., “k-Norm Misclassification Rate Estimation for Decision Trees”, Proceedings of the 11th IASTED International Conference on Artificial Intelligence and Soft Computing (ASC 2007), pp. 163–168, 2007.
A. Kaylani, Georgiopoulos, M., Mollaghasemi, M., and Anagnostopoulos, G. C., “M-GFAM:An Elegant Approach to Genetically Optimize Fuzzy ARTMAP Neural Network Architectures”, Proceedings of the 8th International Conference on Natural Computing (ICNC 2007),part of the 10th Joint Conference on Information Sciences (JCIS 2007), pp. 1617-1623, 2007.
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.
J. Castro, Secretan, J., Georgiopoulos, M., DeMara, R., Anagnostopoulos, G. C., and Gonzalez, A., “Pipelining of Fuzzy ARTMAP without Matchtracking: Correctness,Performance Bound and Beowulf Evaluation”, Neural Networks, vol. 20.1, pp. 109–128, 2007.
J. Secretan, Georgiopoulos, M., and Castro, J., “A Privacy Preserving Probabilistic Neural Network for Horizontally Partitioned Databases”, 2007.
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.
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.
A. Gonzalez, Georgiopoulos, M., and DeMara, R., “Using Context-Based Neural Networks to Maintain Coherence Among Entities’ States in a Distributed Simulation”, The Journal of Defense Modeling and Simulation, vol. 4, pp. 147-172, 2007.
A. Gonzalez, Georgiopoulos, M., and DeMara, R., “Using context-based neural networks to maintain coherence in distributed simulations”, The Journal of Defense Modeling and Simulation, vol. 4, pp. 417-172, 2007.
2008
J. R. Beck, Garcia, M. E., Zhong, M., Georgiopoulos, M., and Anagnostopoulos, G. C., “A Backward adjusting strategy for the C4.5 decision tree classifier, and the effect of the C4.5 parameters on the tree’s performance”, in 21st Artificial Intelligence Research Symposium, Coconut Grove, FL, 2008.
D. Charalampidis, Anagnostopoulos, G. C., Kasparis, T., and Georgiopoulos, M., “Classification of noisy patterns using ARTMAP-based neural networks”, Proceedings SPIE; Conference on Visual Information Processing IX, pp. 2-13, 2008.
A. Koufakou, Georgiopoulos, M., and Anagnostopoulos, G. C., “Detecting Outliers in High-Dimensional Datasets with Mixed Attributes”, International Conference on Data Mining (DMIN 2008), 2008.
A. Kaylani, Georgiopoulos, M., Mollaghasemi, M., and Anagnostopoulos, G., “Efficient Evolution of ART Neural Networks”, in 2008 IEEE Congress on Evolutionary Computation (IEEE CEC 2008), 2008.
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.
S. Verzi, Heileman, G., Georgiopoulos, M., and Healy, M., “Hierarchical ARTMAP”, Proceedings of the International Joint Conference on Neural Networks (IJCNN), pp. 41–46, 2008.
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.
M. Zhong, Georgiopoulos, M., and Anagnostopoulos, G. C., “A k -norm pruning algorithm for decision tree classifiers based on error rate estimation”, Machine Learning, vol. 71, pp. 55-88, 2008.
A. Kaylani, Georgiopoulos, M., Mollaghasemi, M., and Anagnostopoulos, G., “MO-GART: Multi-Objective Optimization of ART Architectures”, in 2008 IEEE Congress on Evolutionary Computation (IEEE CEC 2008), Hong Kong, 2008.
D. Charalampidis, Kasparis, T., Jones, L., and Georgiopoulos, M., “Use of multifractals to detect anomalous propagation (AP) in weather radar”, Proceedings SPIE; Conference on Signals and Data Processing of Small Targets, pp. 13–22, 2008.
2009
A. Kaylani, Georgiopoulos, M., Mollaghasemi, M., and Anagnostopoulos, G., “AG-ART: An Adaptive Method of Evolving ART Architectures”, Neurocomputing, vol. 72, pp. 2079-2092, 2009.
J. Secretan, Koufakou, A., and Georgiopoulos, M., “APHID: A practical architecture for high-performance, privacy preserving, data-mining”, in DMIN 2009, Las Vegas,NV, 2009.
C. Sentelle, Anagnostopoulos, G. C., and Georgiopoulos, M., “An efficient active set method for SVM training without singular inner problems”, in the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN 2009), Atlanta, GA, 2009.
C. Sentelle and G.C. Anagnostopoulos, G. M., “A Fast Revised Simplex Method for SVM Training”, ICPR, 2009.
M. Georgiopoulos, DeMara, R. F., Gonzalez, A. J., Wu, A. S., Mollaghasemi, M., Gelenbe, E., Kysilka, M., Secretan, J., Sharma, C. A., and Alnsour, A. J., “A Sustainable Model for Integrating Current Topics in Machine Learning Research in the Undergraduate Curriculum”, IEEE Transactions on Education, vol. 52, pp. 503-512, 2009.
2010
J. Secretan, Koufakou, A., Georgiopoulos, M., and Cardona, K., “APHID: An architecture for private, high-performance integrated data-mining”, Journal of Future Generation Computer Systems, vol. 26, pp. 891-904, 2010.
A. Koufakou and Georgiopoulos, M., “A fast outlier detection strategy for distributed high dimensional datasets with mixed attributes”, Data Mining and Knowledge Discovery, vol. 20, pp. 259-289, 2010.
R. Miguez, Georgiopoulos, M., and Kaylani, A., “A Genetically Engineered Probabilistic Neural Network”, Nonlinear Analysis: Theory, Methods & Applications, vol. 73, pp. 1783-1791, 2010.
C. Puklavage, Pirela, A., Gonzalez, A. J., and Georgiopoulos, M., “Imitating personalized expressions through an Avatar using Machine Learning”, in Proceedings of the 23rd International FLAIRS conference, 2010.
M. Dagley-Falls, Georgiopoulos, M., and Young, C., “Influencing sense of community in a STEM living-learning community: An NSF STEP funded project”, in Proceedings of the 2010 ASEE Conference and Exposition, 2010.
M. Georgiopoulos, Li, C., and Kocak, T., “Learning in the Feed-Forward Random Neural Network: A Critical Review”, in the 25th International Symposium on Computer and Information Sciences, London, UK, 2010.
M. Georgiopoulos, Li, C., and Kocak, T., “Learning in the Feed-Forward Random Neural Network: A Critical Review”, Performance Evaluation, 2010.
A. Kaylani, Georgiopoulos, M., Mollaghasemi, M., and Anagnostopoulos, G., “MO-GART: An adaptive multi-objective approach to evolving ART architectures”, IEEE Transactions on Neural Networks, vol. 21, pp. 529-550, 2010.
A. Kaylani, Georgiopoulos, M., Mollaghasemi, M., and Anagnostopoulos, G., “MO-GART: An adaptive multi-objective approach to evolving ART architectures”, IEEE Transactions on Neural Networks, vol. 21, pp. 529-550, 2010.
A. Koufakou, Secretan, J., and Georgiopoulos, M., “Non-derivable itemsets for fast outlier detection in large high dimensional categorical data”, Knowledge and Information Systems, pp. 1-29, 2010.
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.
2011
Y.Huang, M. Georgiopoulos, R. DeMara,, and G.C. Anagnostopoulos, M. Georgiopoulos, “Accelerated Learning of Generalized Sammon Mappings”, in International Joint Conference on Neural Networks (IJCNN), San Jose, CA, 2011.
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.
C.Li, M. Georgiopoulos, R. DeMara,, and G.C. Anagnostopoulos, M. Georgiopoulos, “Kernel Principal Subspace Mahalanobis Distances for Outlier Detection”, in International Joint Conference on Neural Networks (IJCNN), San Jose, CA, 2011.
M. Georgiopoulos, Li, C., and Kocak, T., “Learning in the Feed-Forward Random Neural Network: A Critical Review”, Performance Evaluation, vol. 68, pp. 361-384, 2011.
T.Rubio, Zhang, T., Georgiopoulos, M., and Kaylani, A., “Multi-Objective Evolutionary Optimization of Exemplar-Based Classifiers: A PNN Test Case”, in International Joint Conference on Neural Networks (IJCNN), San Jose, CA, 2011.
2012
L. Massi, Lancey, P., Nair, U., Straney, R., Georgiopoulos, M., and Young, C., “Engineering and Computer Science Community College Transfers and Native Freshmen Students: Relationships Among Participation in Extra-Curricular and Co-Curricular Activities, Connecting to the University Campus, and Academic Success”, in Frontiers in Education Conference, Seattle, WA, October 3-6, 2012.
T. Zhang, Borrero, G., and Georgiopoulos, M., “A Winner-Take-All Methodology: Finding the Best Evolutionary Algorithm for the Global Optimization of Functions”, Genetic and Evolutionary Computation Conference. Philadelphia, July 7th-July 11th, pp. 1515-1516, 2012.
2013
L. Massi, Georgiopoulos, M., Young, C. Y., Ford, C. M., Lancey, P., Bhati, D., and Small, K. A., “Internships and Undergraduate Research: Impact, Support, and Institutionalization of an NSF S-STEM Program through Partnerships with Industry and Funding from Federal and Local Workforce Agencies”, Proceedings of the 120th ASEE Conference and Exposition. Atlanta, GA, June 23-26, 2013.
C. Li, Georgiopoulos, M., and Anagnostopoulos, G. C., “Kernel-based Distance Metric Learning in the Output Space”, in International Joint Conference on Neural Networks (IJCNN), Dallas, TX, August 04-09, 2013.
Y. Huang, Li, C., Georgiopoulos, M., and Anagnostopoulos, G. C., “Reduced Rank Local Distance Metric Learning”, in European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML and PKDD 2013), Prague, Czech Republic, September 23-27, 2013.
T. Zhang, Georgiopoulos, M., and Anagnostopoulos, G. C., “S-RACE: A Multi-objective Racing Algorithm”, GECCO 2013, Proceedings of the fifteenth annual conference on Genetic and evolutionary computation conference. Amsterdam, the Netherlands, July 6-10, pp. 1565-1572, 2013.
2014
C. Li, Georgiopoulos, M., and Anagnostopoulos, G. C., “Conic Multi-Task Classification”, in ECML PKDD 2014, Nancy, France, September 15-19, 2014.
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.
C. Li, Georgiopoulos, M., and Anagnostopoulos, G. C., “Multi-Task Classification Hypothesis Space with Improved Generalization Bounds ”, IEEE Transactions on Neural Networks and Learning Systems, vol. accepted for publication (acceptance was communicated in July 2014), 2014.
T. Zhang, Georgiopoulos, M., and Anagnostopoulos, G. C., “Online Model Racing Based on Extreme Performance”, in GECCO 2014, Vancouver, Canada, July 12-16, 2014, accepted for publication, 2014.
C. Li, Georgiopoulos, M., and Anagnostopoulos, G. C., “Pareto-Path Multi-task Multiple Kernel Learning”, IEEE Transactions on Neural Networks and Learning Systems, vol. accepted for publication (acceptance was communicated in June 2014), 2014.
C. Li, Georgiopoulos, M., and Anagnostopoulos, G. C., “A Unifying Framework for Typical Multitask, Multiple Kernel Learning Problems”, IEEE Transactions on Neural Networks and Learning Systems, vol. 25, no. 7, pp. 1287-1297, 2014.
2015
T. Zhang, M. Georgiopoulos, R. DeMara,, and Anagnostopoulos, G. C., “Multi-Objective Model Selection via Racing”, IEEE Transactions on Cybernetics, vol. 46, no. 8, pp. 1863-1876, 2015.
C. Li, M. Georgiopoulos, R. DeMara,, and Anagnostopoulos, G. C., “Multi-Task Classification Hypothesis Space with Improved Generalization Bounds”, IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 7, pp. 1468-1479, 2015.
C. Li, M. Georgiopoulos, R. DeMara,, and Anagnostopoulos, G. C., “Pareto-Path Multi-Task Multiple Kernel Learning”, IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 1, pp. 51-61, 2015.
2016
C. Sentelle, Anagnostopoulos, G. C., and M. Georgiopoulos, R. DeMara, “A Simple Method for Solving the SVM Regularization Path for Semi-Definite Kernels”, IEEE Transactions on Neural Networks and Learning Systems, vol. 27, no. 4, pp. 709-722, 2016.
2018
T. Zhang, M. Georgiopoulos, R. DeMara,, and Anagnostopoulos, G. C., “Pareto Optimal Selection via SPRINT-Race”, IEEE Transactions on Cybernetics, vol. 48, no. 2, pp. 596-610, 2018.

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