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68T05 Learning and adaptive systems (43 articles)

• Pestov, Vladimir G.: On a result of K. P. Hart about non-existence of measurable solutions to the discrete expectation maximization problem. (English). Commentationes Mathematicae Universitatis Carolinae, vol. 64 (2023), issue 3, pp. 353-358
• Agapie, Alexandru; Wright, Alden H.: Theoretical analysis of steady state genetic algorithms. (English). Applications of Mathematics, vol. 59 (2014), issue 5, pp. 509-525
• Malvestuto, Francesco M.: A backward selection procedure for approximating a discrete probability distribution by decomposable models. (English). Kybernetika, vol. 48 (2012), issue 5, pp. 825-844
• Nagy, Ivan; Suzdaleva, Evgenia; Kárný, Miroslav: Bayesian estimation of mixtures with dynamic transitions and known component parameters. (English). Kybernetika, vol. 47 (2011), issue 4, pp. 572-594
• Juríček, Jozef: Maximization of the information divergence from multinomial distributions. (English). Acta Universitatis Carolinae. Mathematica et Physica, vol. 52 (2011), issue 1, pp. 27-35
• Theodoridis, Dimitris; Boutalis, Yiannis; Christodoulou, Manolis: Direct adaptive control of unknown nonlinear systems using a new neuro-fuzzy method together with a novel approach of parameter hopping. (English). Kybernetika, vol. 45 (2009), issue 3, pp. 349-386
• Torra, Vicenç; Endo, Yasunori; Miyamoto, Sadaaki: On the comparison of some fuzzy clustering methods for privacy preserving data mining: Towards the development of specific information loss measures. (English). Kybernetika, vol. 45 (2009), issue 3, pp. 548-560
• Baronas, Romas; Ivanauskas, Feliksas; Maslovskis, Romualdas; Radavičius, Marijus; Vaitkus, Pranas: Locally weighted neural networks for an analysis of the biosensor response. (English). Kybernetika, vol. 43 (2007), issue 1, pp. 21-30
• Révayová, Martina; Török, Csaba: Piecewise approximation and neural networks. (English). Kybernetika, vol. 43 (2007), issue 4, pp. 547-559
• Bodenhofer, Ulrich; Bauer, Peter: Interpretability of linguistic variables: a formal account. (English). Kybernetika, vol. 41 (2005), issue 2, pp. [227]-248
• Kůrková, Věra: Učení neuronových sítí jako inverzní úloha. (Czech) [Neural nets learning as an inverse problem]. Pokroky matematiky, fyziky a astronomie, vol. 49 (2004), issue 3, pp. 218-225
• Vomlel, Jiří: Building adaptive tests using Bayesian networks. (English). Kybernetika, vol. 40 (2004), issue 3, pp. [333]-348
• Železný, Filip: Efficiency-conscious propositionalization for relational learning. (English). Kybernetika, vol. 40 (2004), issue 3, pp. [275]-292
• Vojtáš, Peter; Horváth, Tomáš; Krajči, Stanislav; Lencses, Rastislav: An ILP model for a monotone graded classification problem. (English). Kybernetika, vol. 40 (2004), issue 3, pp. [317]-332
• Allende, Héctor; Moraga, Claudio; Salas, Rodrigo: Artificial neural networks in time series forecasting: a comparative analysis. (English). Kybernetika, vol. 38 (2002), issue 6, pp. [685]-707
• Abdallah, Chaouki T.; Ariola, Marco; Koltchinskii, Vladimir: Statistical-learning control of multiple-delay systems with application to ATM networks. (English). Kybernetika, vol. 37 (2001), issue 3, pp. [355]-365
• Marsala, Christophe: Fuzzy decision trees to help flexible querying. (English). Kybernetika, vol. 36 (2000), issue 6, pp. [689]-705
• Vajda, Igor; Grim, Jiří: About the maximum information and maximum likelihood principles. (English). Kybernetika, vol. 34 (1998), issue 4, pp. [485]-494
• Alpaydin, Ethem; Kaynak, Cenk: Cascading classifiers. (English). Kybernetika, vol. 34 (1998), issue 4, pp. [369]-374
• Pudil, Pavel; Novovičová, Jana; Somol, Petr; Vrňata, Radek: Conceptual base of feature selection consulting system. (English). Kybernetika, vol. 34 (1998), issue 4, pp. [451]-460
• Sato, Manabu; Kudo, Mineichi; Toyama, Jun; Shimbo, Masaru: Construction of nonlinear discrimination function based on the MDL criterion. (English). Kybernetika, vol. 34 (1998), issue 4, pp. [467]-472
• Kumar, Rajeev; Rockett, Peter: Decomposition of high dimensional pattern spaces for hierarchical classification. (English). Kybernetika, vol. 34 (1998), issue 4, pp. [435]-442
• Duin, Robert P. W.; de Ridder, Dick; Tax, David M. J.: Featureless pattern classification. (English). Kybernetika, vol. 34 (1998), issue 4, pp. [399]-404
• Raudys, Šarūnas: Intrinsic dimensionality and small sample properties of classifiers. (English). Kybernetika, vol. 34 (1998), issue 4, pp. [461]-466
• Grim, Jiří: Mixture of experts architectures for neural networks as a special case of conditional expectation formula. (English). Kybernetika, vol. 34 (1998), issue 4, pp. [417]-422
• Vajda, Igor; Lonek, Belomír; Nikolov, Viktor; Veselý, Arnošt: Neural network realizations of Bayes decision rules for exponentially distributed data. (English). Kybernetika, vol. 34 (1998), issue 5, pp. [497]-514
• Haindl, Michal; Šimberová, Stanislava: A scratch removal method. (English). Kybernetika, vol. 34 (1998), issue 4, pp. [423]-428
• Case, John; Jain, Sanjay; Ngo Manguelle, Suzanne: Refinements of inductive inference by Popperian and reliable machines. (English). Kybernetika, vol. 30 (1994), issue 1, pp. 23-52
• Geyer-Schulz, Andreas: On learning in a fuzzy rule-based expert system. (English). Kybernetika, vol. 28 (1992), issue 7, pp. 33-36
• Vasilakos, A. V.; Haritsis, A.; Batistatos, S.: Isarithmic flow control using learning automata. (English). Kybernetika, vol. 26 (1990), issue 6, pp. 473-483
• Vasilakos, Athanasios V.: On the behaviour of learning algorithms in a changing environment with application to data network routing problem. (English). Kybernetika, vol. 26 (1990), issue 4, pp. 296-307
• Le Minh Trung: The order of node removals in influence diagram. (English). Kybernetika, vol. 25 (1989), issue 7, pp. 20-24
• Havránek, Tomáš: Some notes to the algebraization of Dempster-Shafer treatment of uncertainty. (English). Kybernetika, vol. 25 (1989), issue 7, pp. 10-14
• Sallantin, Jean; Van der Pyl, Thierry: On the Bayesian inductive processes. (English). Kybernetika, vol. 19 (1983), issue 4, pp. 319-334
• Bláha, Svatopluk: Comment on “Convergence properties of adaptive threshold elements...”. (English). Kybernetika, vol. 17 (1981), issue 2, pp. 183-185
• Schoenborn, Werner; Stanke, Gerd: Convergence properties of adaptive threshold elements in respect to application and implementation. (English). Kybernetika, vol. 16 (1980), issue 2, pp. (159)-171
• Brůha, Ivan: Learning extremal regulator implementation by a stochastic automaton and stochastic approximation theory. (English). Aplikace matematiky, vol. 25 (1980), issue 5, pp. 315-323
• Kramosil, Ivan: Mechanized experiment planning in automaton-environment systems. (English). Kybernetika, vol. 13 (1977), issue 4, pp. (225)-244
• Pugachev, V. S.: Optimal learning systems. (English). Kybernetika, vol. 7 (1971), issue 5, pp. (347)-376
• Brody, Jozef: Error frequency - regulator of the teaching algorithm. (English). Kybernetika, vol. 4 (1968), issue 6, pp. (548)-569
• Plander, Ivan: Teoretické problémy technickej kybernetiky. (Slovak) [Theoretical problems of technical cybernetics]. Kybernetika, vol. 2 (1966), issue 4, pp. (355)-360
• Petráš, Štefan: Učiace sa systémy automatického riadenia. (Slovak) [Learning systems of automatic control]. Kybernetika, vol. 2 (1966), issue 4, pp. (361)-373
• Mleziva, Miroslav: K teorii konečných automatů (neuronových sítí). (Czech) [On the theory of finite automata (neural networks)]. Pokroky matematiky, fyziky a astronomie, vol. 5 (1960), issue 6, pp. 643-668