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Author Title [ Type(Desc)] Year
Conference Proceedings
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.
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.
Journal Article
N. Shorter and Kasparis, T., “3D Reconstruction of Irregular Spaced LIDAR”, Proceedings of the 6th WSEAS International Conference on Systems Theory and Scientific Computation, 2006.
E. A. H. Zooghby, Christodoulou, C. G., and Georgiopoulos, M., “Adaptive interference cancellation in circular arrays with radialbasis function neural networks”, IEEE Antennas and Propagation Society International Symposium, 1998.
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.
C. S. Ho, Liou, J. J., Georgiopoulos, M., Heileman, G. L., and Christodoulou, C., “Analog circuit design and implementation of an adaptive resonance theory (ART) neural network architecture”, International Journal of Electronics, vol. 76, pp. 271-291, 1994.
J. Castro, Georgiopoulos, M., and Secretan, J., “Analyzing the Fuzzy ARTMAP Matchtracking mechanism with Co-Objective Optimization Theory”, Proceedings of the International IEEE-INNS-ENNS Joint Conference on Neural Networks (IJCNN), pp. 743–748, 2007.
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.
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.
M. Mollaghasemi, LeCroy, K., and Georgiopoulos, M., “Application of neural networks and simulation modeling in manufacturing system design”, INTERFACES, vol. 28, pp. 100-114, 1998.
A. J. Gonzaleza, Georgiopoulos, M., DeMara, R. F., Henninger, A., and Gerber, W., “Automating the CGF Model Development and Refinement Process by Observing Expert Behavior in a Simulation”, 7th Conference on Computer Generated Forces and Behavioral Representation, 1998.
G. Bebis, Papadourakis, G. M., and Georgiopoulos, M., “Back-Propagation: Increasing rate of convergence by predictable pattern loading”, vol. 1, pp. 14-30, 1989.
A. Henninger, Gerber, W., DeMara, R., Georgiopoulos, M., and Gonzalez, A., “Behavior Modeling Framework for Embedded Simulation”, Interservice/Industry Training,Simulation & Education Conference (I/ITSEC 98), pp. 655–662, 1998.
S. J. Verzi, Heileman, G. L., Georgiopoulos, M., and Healy, M. J., “Boosted ARTMAP”, IEEE International Joint Conference on Neural Networks, pp. 396–401, 1998.
S. Verzi, Heileman, G. L., and Georgiopoulos, M., “Boosted ARTMAP: Modifications to fuzzy ARTMAP motivated by boosting Theory”, Neural Networks, vol. 19.4, pp. 446–468, 2006.
G. C. Anagnostopoulos, Georgiopoulos, M., Verzi, S., and Heileman, G., “Boosted ellipsoid ARTMAP”, Proceedings of SPIE,Conference on Applications and Science of Computational Intelligence, vol. 4739, pp. 74–85, 2002.
J. Secretan, Lawson, M., and Boloni, L., “Brokering Algorithms for Composing Low Cost Distributed Storage Resources”, 2007.
G. C. Anagnostopoulos and Georgiopoulos, M., “Category regions as new geometrical concepts in Fuzzy-ART and Fuzzy-ARTMAP”, Neural Networks, vol. 15.10, pp. 1205-1221, 2002.
W. D. Jr., Liou, J. J., and Georgiopoulos, M., “Circuit simulation of adaptive resonance (ART) neural networks using PSpice”, International Journal of Electronics, vol. 74, pp. 101-110, 1993.
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.
D. Chralampidis, Kasparis, T., and Georgiopoulos, M., “Classification of noisy signals using fuzzy ARTMAP neural networks”, Neural Networks, vol. 12.5, pp. 1023–1036, 2001.
D. Charalampidism, Georgiopoulos, M., and Kasparis, T., “Classification of Noisy Signals Using Fuzzy ARTMAP Neural Networks”, Proceedings of the International Joint Conference on Neural Networks (IJCNN), pp. 53–58, 2000.
M. Georgiopoulos and Papantoni-Kazakos, P., “Collision resolution algorithms utilizing absorptions and collision multiplicities”, IEEE Trans. on Comm., vol. 33, pp. pp. 401-404, 1985.
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.
A. Koufakou, Weihs, N., Georgiopoulos, M., and Al-Daraiseh, A., “Comparisons of Gaussian ARTMAP and Distributed Gaussian ARTMAP Classifiers - The Category Proliferation Problem”, Evolutionary Programming,Complex Systems and Artificial Life also presented at the 2006 Artificial Neural Networks in Engineering (ANNIE), vol. 16, pp. 695–704, 2006.
A. Henninger, Gonzalez, A., Georgiopoulos, M., and DeMara, R., “A connectionist-symbolic approach to modeling agents: Neural networks grouped by contexts”, Proceedings of the CONTEXT-01 Conference, pp. 198–209, 2001.
A. J. Gonzalez, Gerber, W. J., DeMara, R. F., and Georgiopoulos, M., “Context-driven Near-term Intention Recognition”, Journal of Defense Modeling and Simulation, vol. 1.3, pp. 153–170, 2004.
M. Georgiopoulos, Heileman, G. L., and Huang, J., “Convergence properties of learning in ART1”, Neural Computation, vol. 2, pp. 502-510, 1990.
M. Georgiopoulos, “Correction to ‘Packet error probabilities in frequency hopped spread-spectrum packet radio networks-memoryless frequency hopping patterns considered’”, IEEE Trans. on Comm., vol. 39, pp. 362-364, 1991.
G. Bebis, Georgiopoulos, M., and Kasparis, T., “Coupling weight elimination with genetic algorithms to reduce network size and preserve generalization”, Neurocomputing, pp. 167–194, 1997.
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.
M. Georgiopoulos, Castro, J., Gelenbe, E., DeMara, R., Gonzalez, A., and Kysilka, M., “CRCD Experiences at the University of Central Florida: An NSF Project”, Proceedings of the ASEE 2004 Annual Conference and Exposition, 2004.
M. Georgiopoulos, Castro, J., Wu, A., DeMara, R., Gelenbe, E., and Gonzalez, A., “CRCD in machine learning at the University of Central Florida preliminary experiences”, Proceedings of the 8th annual conference on Innovation and Technology in Computer Science Education, p. 249, 2003.
A. Koufakou, Georgiopoulos, M., Anagnostopoulos, G. C., and Kasparis, T., “Cross-validation in Fuzzy ARTMAP for large databases”, Neural Networks, vol. 14.9, pp. 1279-1291, 2001.
M. Georgiopoulos, Koufakou, A., Anagnostopoulos, G. C., and Kasparis, T., “Cross-Validation in Fuzzy ARTMAP Neural Networks for Large Sample Classification Problems”, Proceedings of SPIE; Applications and Science of Computational Intelligence IV, 2001.
J. Castro, Georgiopoulos, M., DeMara, R., and Gonzalez, A., “A data partitioning approach to speed the Fuzzy ARTMAP algorithm using the Hilbert space-filling curve”, pp. 2367–2372, 2004.
J. Castro, Georgiopoulos, M., DeMara, R., and Gonzalez, A., “Data-partitioning using the Hilbert space filling curves Effect on the speed of convergence of Fuzzy ARTMAP for large database problems”, Neural Networks, vol. 18, pp. 967-984, 2005.
J. Castro, Georgiopoulos, M., DeMara, R., and Gonzalez, A., “Data-partitioning using the Hilbert space filling curves: Effect on the speed of convergence of Fuzzy ARTMAP for large database problems”, Neural Networks, vol. 18.7, pp. 967–984, 2005.
C. Christodoulou, Huang, J., and Georgiopoulos, M., “Design of gratings and frequency-selective surfaces using ARTMAP neural networks”, Journal of Electromagnetic Waves and Applications, vol. 9, pp. 17-36, 1995.
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.
J. Klodzinski, Al-Daraiseh, A., Georgiopoulos, M., and Al-Deek, H. M., “Development of a java applet for generating truck trips from freight data”, Transportation Research Record No. 1870, pp. 10–17, 2004.
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.
G. L. Heileman, Georgiopoulos, M., and Abdallah, C., “A dynamical adaptive resonance architecture”, IEEE Transactions on Neural Networks, vol. 5, pp. 873-889, 1994.
G. C. Anagnostopoulos and Georgiopoulos, M., “Ellipsoid ART and ARTMAP for incremental clustering and classification”, Proceedings of the International Joint Conference on Neural Networks, pp. 1221–1226, 2001.
G. C. Anagnostopoulos and Georgiopoulos, M., “Ellipsoid ART and ARTMAP for incremental unsupervised and supervised Learning”, Proceedings of SPIE; Conference on Applications and Science of Computational Intelligence IV, pp. 293–304, 2001.
G. C. Anagnostopoulos and Georgiopoulos, M., “Ellipsoid ART/ARTMAP category regions for the choice-by-difference functions”, Proceedings of SPIE,Conference on Applications and Science of Computational Intelligence V, vol. 4739, pp. 62–73, 2002.
M. Georgiopoulos, “On the error probability of coded frequency hopped spread spectrum multiple access systems with more than one code symbols per dwell interval”, IEEE Trans. on Comm., vol. 38, pp. 1321-1324, 1990.
G. C. Anagnostopoulos, Bharadwaj, M., Georgiopoulos, M., Verzi, S., and Heileman, G., “Exemplar-based pattern recognition via semi-supervised learning”, Neural Networks, pp. 2782–2787, 2003.
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.
C. Sentelle, Georgiopoulos, M., Anagnostopoulos, G. C., and Young, C., “On extending the SMO algorithm sub-problem”, Proceedings of the International Joint Conference on Neural Networks (IJCNN), 2007.
G. Bebis, Uthiram, S., and Georgiopoulos, M., “Face detection and verification using genetic search”, International Jornal on Artificial Intelligence Tools, vol. 9.2, pp. 225–245, 2000.
A. Meyer-Base, Jancke, K., Wissmuller, A., and Georgiopoulos, M., “Fast K-dimensional tree-structured vector quantization encoding method for image compression”, Optical Engineering Letters, vol. 43, pp. 1012-1013, 2004.
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.
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.
C. Sentelle and G.C. Anagnostopoulos, G. M., “A Fast Revised Simplex Method for SVM Training”, ICPR, 2009.
K. Carr, Cannava, K., Pescatore, R., Georgiopoulos, M., and Anagnostopoulos, G. C., “Fast Stable and on-line training of Fuzzy ARTMAP using a novel,conservative,slow learning strategy”, Neural Networks, pp. 63–69, 2004.
A. Henninger, Gonzalez, A., Gerber, W., Georgiopoulos, M., and DeMara, R., “On the Fidelity of SAFs: Can performance data help?”, Proceedings of the 2000 Interservice/Industry Training,Simulation and Education Conference (I/ITSEC-2000), pp. 147–154, 2000.
G. Bebis, Deaconu, T., and Georgiopoulos, M., “Fingerprint identification using Delaunay triangulation”, IEEE International Conference on Information,Intelligence and Systems, pp. 452–459, 1999.
D. Charalampidis, Anagnostopoulos, G. C., Georgiopoulos, M., and Kasparis, T., “Fuzzy ART and ARTMAP with adaptive weighted distances”, Proceedings of SPIE,Conference on Applications and Science of Computational Intelligence V, vol. 4739, pp. 86–97, 2002.
J. Huang, Georgiopoulos, M., and Heileman, G. L., “Fuzzy ART properties”, Neural Networks, vol. 8, pp. 203-213, 1995.
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.
I. Dagher, Georgiopoulos, M., Heileman, G., and Bebis, G., “Fuzzy ARTVar: An Improved Fuzzy ARTMAP Algorithm”, International Joint Conference on Neural Networks, pp. 1688–1693, 1998.
C. Sentelle, Hong, S. L., Anagnostopoulos, G. C., and Georgiopoulos, M., “A fuzzy gap statistic for Fuzzy C-Means”, Proceedings of the 11th IASTED International Conference on Artificial, 2007.
N. Shorter and Kasparis, T., “Fuzzy SART Clustering for 3D Reconstruction from Irregular LIDAR Data”, vol. 2.8, pp. 1122 – 1129, 2006.
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.
M. Zhong, Georgiopoulos, M., Anagnostopoulos, G. C., and Mollaghasemi, M., “Generalized Entropy for Splitting Numerical Attributes in Decision Tree Classifiers”, Proceedings of the 19th International Florida Artificial Intelligence Research Society (FLAIRS) Conference (FLAIRS 2006), pp. 604–609, 2006.
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.
A. Kaylani, Al-Daraiseh, A., Georgiopoulos, M., Mollaghasemi, M., Anagnostopoulos, G. C., and Wu, A. S., “Genetic Optimization of ART Neural Network Architectures”, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN 2007), pp. 379–384, 2007.
G. Bebis, Uthiram, S., and Georgiopoulos, M., “Genetic Search for Face Detection and Verification”, IEEE International Conference on Information,Intelligence and Systems, pp. 360–367, 1999.
A. Al-Daraiseh, Kaylani, A., Georgiopoulos, M., Mollaghasemi, M., Anagnostopoulos, G. C., and Kaburlasos, V. G., “Genetically Engineered ART Architectures”, Heidelberg: Springer-Verlag,in Computational Intelligence Based on Lattice Theory,Studies in Computational Intelligence, vol. 67, pp. 233–262, 2007.
R. Miguez, Georgiopoulos, M., and Kaylani, A., “A Genetically Engineered Probabilistic Neural Network”, Nonlinear Analysis: Theory, Methods & Applications, vol. 73, pp. 1783-1791, 2010.
A. Al-Dairaiseh, Kaylani, A., Georgiopoulos, M., Mollaghasemi, M., Wu, A. S., and Anagnostopoulos, G., “GFAM Evolving Fuzzy ARTMAP Neural Networks”, Neural Networks journal, vol. 20, pp. 874-892, 2007.
A. Al-Daraiseh, Kaylani, A., Georgiopoulos, M., Wu, A. S., Mollaghasemi, M., and Anagnostopoulos, G. C., “GFAM:Evolving Fuzzy ARTMAP Neural Networks”, vol. 20.8, pp. 874–892, 2007.
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.
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.
G. C. Anagnostopoulos and Georgiopoulos, M., “Hypersphere ART and ARTMAP for Unsupervised and Supervised,Incremental Learning”, Proceedings of the International Joint Conference on Neural Networks (IJCNN), pp. 59–64, 2000.
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.
G. Bebis, Georgiopoulos, M., Shah, M., and da Lobo, V. N., “Indexing Based on Algebraic Functions of Views”, Computer Vision and Image Understanding, vol. 72.3, pp. 360–378, 1998.
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.
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.
G. Bebis, Georgiopoulos, M., da Lobo, V. N., and Shah, M., “Learning affine transformations”, Pattern Recognition, vol. 32.10, pp. 1783–1799, 1999.
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.
M. Georgiopoulos, Li, C., and Kocak, T., “Learning in the Feed-Forward Random Neural Network: A Critical Review”, Performance Evaluation, 2010.
H. K. Fernlund, Gonzalez, A. J., Georgiopoulos, M., and DeMara, R., “Learning tactical human behavior through observation of human performance”, Cybernetics–Part B: Cybernetics,Man,IEEE Transactions on Systems, vol. 36.1, pp. 128–140, 2006.
A. Henninger, Gonzalez, A., Georgiopoulos, M., and DeMara, R., “The Limitations of Static Performance Metrics for Dynamic Tasks Learned Through Observation”, Proceedings of the Tenth Conference on Computer Generated Forces and Behavioral Representation, pp. 147–154, 2001.
J. Secretan, Georgiopoulos, M., Maidhof, I., Shibly, P., and Hecker, J., “Methods for Parallelizing the Probabilistic Neural Network on a Beowulf Cluster Computer”, 2006.
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.
A. Henninger, Gonzalez, A., Georgiopoulos, M., and DeMara, R., “Modeling Semi-Automated Forces with Neural Networks: Performance Improvement through a Modular Approach”, 2000.
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.
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.
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.
E. A. H. Zooghby, Christodoulou, C. G., and Georgiopoulos, M., “Multiple mobile user tracking with neural network-based adaptive array antennas”, SPIE Conference on Digital Wireless Communications, pp. 88–97, 1999.
C. Christodoulou, Georgiopoulos, M., and Zooghby, E. A., “Multiple Source Angle of Arrival Estimation using Neural-Network-based Smart Antennas”, Proceedings SPIE; Conference on Digital Wireless Communications II, pp. 94–99, 2000.
E. A. H. Zooghby, Christodoulou, C. G., and Georgiopoulos, M., “Multiple sources neural network direction finding with arbitrary separations”, IEEE-APS Conference on Antennas and Propagation for Wireless Communications, pp. 57–60, 1998.
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.

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