Šarūno Raudžio svarbiausios publikacijos

S. Raudys, A. Raudys. Pair-wise costs in multi-class peceptrons. IEEE Transactions on Pattern Analysis and Machine Intelligence (ISSN 0162-8828), vol. 32, pp. 1324-1328, 2010. SRaudys_1
S. Raudys. Experts' boasting in trainable fusion rules. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, pp. 1178-1182, 2003. SRaudys_2
S. Raudys and A. Saudargiene. First-order tree-type dependence between variables and classification performance. IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 23, pp. 1324-1328, 2001. SRaudys_3
S. Raudys. On dimensionality, sample size and classification error of nonparametric linear classification algorithms IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 19, pp. 669-671, 1997. SRaudys_4
S. Raudys, R. Kybartas, E. K. Zavadskas. Complexity and sample-size issues in multi-category nets of single-layer perceptrons. IEEE Trans. on Neural Networks (ISSN 1045-9227), vol. 21, 784-795, 2010. SRaudys_5
M. Skurichina, S. Raudys, R.P.W. Duin. K-nearest neighbors directed noise injection in multilayer perceptron training IEEE Trans. on Neural Networks, vol. 11, 504-511, 2000. SRaudys_6
S. Raudys. Scaled rotation regularization. Pattern Recognition (ISSN 0031-3203), vol. 33, pp. 1989-1998, 2000. SRaudys_7
S. Raudys. Trainable fusion rules. II. Small sample size case. Neural Networks (ISSN 0893-6080), vol. 19, pp. 1517-1527, 2006. SRaudys_8
S. Raudys. Trainable fusion rules. I. Large sample size case. Neural Networks, vol. 19, pp. 1506-1516, 2006. SRaudys_9
S. Raudys. How good are support vector machines? Neural Networks, vol. 13, pp. 9-11, 2000. SRaudys_10
S. Raudys. Evolution and generalization of a single neurone. III. Primitive, regularized, standard, robust and minimax regressions, Neural Networks, vol. 13, pp. 507-523, 2000. SRaudys_11
S. Raudys. Evolution and generalization of a single neurone. II. Complexity of statistical classifiers and sample size considerations, Neural Networks, vol. 11, pp. 297-313, 1998 SRaudys_12
S. Raudys. Evolution and generalization of a single neurone. I. SLP as seven statistical classifiers Neural Networks, vol. 11, pp. 283-296, 1998. SRaudys_13
S. Raudys, R.P.W. Duin. On expected classification error of the Fisher classifier with pseudo-inverse covariance matrix, Pattern Recognition Letters (ISSN 0167-8655), vol. 19, pp. 385-392, 1998. SRaudys_14
T. Cibas, F. Fogelman, P. Gallinari, S. Raudys. Variable selection with neural networks, Neurocomputing (ISSN 0925-2312), vol. 12, pp. 223-248, 1996. SRaudys_15
E.C. Guler, B.Sankur, Y.Kahya, S. Raudys. Two-stage classification of respiratory sound patterns. Computers in Biology and Medicine (ISSN 0010-4825), vol. 35, pp. 67–83, 2005. SRaudys_16
E. Cagatay Guler, B. Sankur, Y. P. Kahya, S. Raudys. Visual classification of medical data using MLP mapping, Computers in Biology and Medicine, vol. 28 272-287, 1998. SRaudys_17
S. Raudys. An adaptation model for simulation of aging process, International Journal of Modern Physics, ser. C (ISSN 0129-1831), vol. 13: 1075-1086, 2002. SRaudys_18
S. Raudys, D.Young. Results in statistical discriminant analysis: A review of the former Soviet Union literature. Journal of Multivariate Analysis (ISSN 0047-259X), vol. 89, pp. 1-35, 2004. SRaudys_19
S. Raudys. Intrinsic dimensionality and small sample size properties of classifiers. Kybernetika (ISSN 0023-5954), vol. 34, pp. 461-466, 1998. SRaudys_20
Ш.Раудис (S. Raudis), В.Юстицкис (V. Yustitskis). Закон Йеркса—Додсона: связь между стимулированием и успешностью научения. Вопросы психологии (Voprosy Psikhologii, ISSN 0042-8841), №3, стр. 119-128, 2008. SRaudys_21
S. Raudys, Statistical and Neural Classifiers: An integrated approach to design. Springer-Verlag. New York. 2001. 312 pages. http://gedmin.as/study/inf98/nn/index-lt.html