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I. Westerlund, G. Von Heijne, and O. Emanuelsson. Lumenp - a neural network predictor for protein localization in the thylakoid lumen. PROTEIN SCI, 12 (10):2360-2366, 2003.

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N. Ampazis, S. J. Perantonis, and J. G. Taylor. A dynamical model for the analysis and acceleration of learning in feedforward networks. Neural Networks, 14 (8):1075-1088, 2001.

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S. J. Perantonis, N. Ampazis, V. Virvilis, and S. Petridis. Open issues in feedforward neural network training. In LFTNC2001, Siena, Italy, 2001.

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A. Agogino, J. Ghosh, S. J. Perantonis, V. Virvilis, S. Petridis, and Lisboa P. J. G. The role of multiple linear-projection based visualization techniques in RBF based classification of high dimensional data. In Proceedings of IEEE-INNS-ENNS IJCNN2000, volume 3, Como, Italy, 2000.

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N. Ampazis and S. J. Perantonis. Levenberg-marquardt algorithm with adaptive momentum for the efficient training of feedforward networks. In Proceedings of IEEE & INNS International Joint Conference on Neural Networks, number NN0401 in 0, Como, Italy, 2000.

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S. J. Perantonis and V. Virvilis. Efficient perceptron learning using constrained steepest descent. Neural Networks, 13(3):351-364, 2000.

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S. J. Perantonis, N Ampazis, and S. Spirou. Training feedforward neural networks with the dogleg method and bfgs hessian updates. Como, Italy, 2000. Submitted to IJCNN' 2000.

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S. J. Perantonis, N. Ampazis, and V. Virvilis. A learning framework for neural networks using constrained optimization methods. In Annals of Operations Research, volume 99, pages 385-401, 2000.

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S. J. Perantonis, S. Petridis, and V. Virvilis. Supervised principal component analysis using a smooth classifier paradigm. In Proceedings of International Conference on Pattern Recognition, number 1572 in 0, Barcelona, Spain, 2000.

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N. Ampazis, S. J. Perantonis, and J. G. Taylor. Acceleration of learning in feedforward networks using dynamical systems analysis and matrix perturbation theory. Washington, DC, 1999. Presented at International Joint Conference on Neural Networks.

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N. Ampazis, S. J. Perantonis, and J. G. Taylor. Dynamics of multilayer networks in the vicinity of temporary minima. Neural Networks, 12 (1):43-58, 1999.

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S. J. Perantonis and V. Virvilis. Dimensionality reduction using a novel neural network based feature extraction method. Washington, DC, 1999. Presented at International Joint Conference on Neural Networks. Best presentation award.

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S. J. Perantonis and V. Virvilis. Input feature extraction for multilayer perceptrons using supervised principal component analysis. Neural Processing Letters, 10(3):243-252, 1999.

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V. Virvilis. Finite Training in Single Layer Perceptrons and Feature Extraction. PhD thesis, University of Athens Department of Informatics, 1999. In greek.

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S. J. Perantonis and V. Virvilis. Efficient linear discriminant analysis using a fast quadratic programming algorithm. In International Workshop on Advanced Black-Box Techniques for Nonlinear Modeling, pages 164-169, Leuven, Belgium, 1998.

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S. J. Perantonis, V. Virvilis, and N. Ampazis. Recent advances in neural network training using constrained optimization. In Proceedings of 4th International Conference on Applied Mathematical Programming and Modeling APMOD98, Limassol, Cyprus, 1998.