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2015 | OriginalPaper | Chapter

13. Measures of Complexity in the Theory of Machine Learning

Author : Alexey Chervonenkis

Published in: Measures of Complexity

Publisher: Springer International Publishing

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Abstract

This text, prepared by the editors, closely follows the abstract (Chervonenkis, Measures of complexity, 2013) and slides of Alexey’s talk at the symposium “Measures of Complexity” (given on Wednesday, October 2, 2013, 2:30–3:20 p.m., in Paphos, Cyprus). (Eds.)

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Literature
1.
go back to reference Chervonenkis, A.Y.: On some properties of classes of events for which the conditions for the uniform convergence of the relative frequencies to probabilities fail to hold. Izv. Math. 76(6), 1271–1285 (2012) (Russian original: Известия PAH, Серия математическая) Chervonenkis, A.Y.: On some properties of classes of events for which the conditions for the uniform convergence of the relative frequencies to probabilities fail to hold. Izv. Math. 76(6), 1271–1285 (2012) (Russian original: Известия PAH, Серия математическая)
2.
go back to reference Chervonenkis, A.Y.: Measures of complexity. In: Papadopoulos, H., Andreou, A.S., Iliadis, L., Maglogiannis, I. (eds.) Artificial Intelligence Applications and Innovations, pp. xvii–xviii. Springer, Heidelberg (2013) Chervonenkis, A.Y.: Measures of complexity. In: Papadopoulos, H., Andreou, A.S., Iliadis, L., Maglogiannis, I. (eds.) Artificial Intelligence Applications and Innovations, pp. xvii–xviii. Springer, Heidelberg (2013)
3.
go back to reference Vapnik, V.N., Chervonenkis, A.Y.: On the uniform convergence of relative frequencies of events to their probabilities. Theory Probab. Appl. 16(2), 264–280 (1971) (This volume, Chap. 3) Vapnik, V.N., Chervonenkis, A.Y.: On the uniform convergence of relative frequencies of events to their probabilities. Theory Probab. Appl. 16(2), 264–280 (1971) (This volume, Chap. 3)
4.
go back to reference Vapnik, V.N., Chervonenkis, A.Y.: Теория распознавания образов: Статистические проблемы обучения (Theory of Pattern Recognition: Statistical Problems of Learning: in Russian). Nauka, Moscow (1974). German translation: Theorie der Zeichenerkennung, transl. K.G. Stöckel and B. Schneider, ed. S. Unger and B. Fritzsch, Akademie Verlag, Berlin (1979) Vapnik, V.N., Chervonenkis, A.Y.: Теория распознавания образов: Статистические проблемы обучения (Theory of Pattern Recognition: Statistical Problems of Learning: in Russian). Nauka, Moscow (1974). German translation: Theorie der Zeichenerkennung, transl. K.G. Stöckel and B. Schneider, ed. S. Unger and B. Fritzsch, Akademie Verlag, Berlin (1979)
5.
go back to reference Vapnik, V.N., Chervonenkis, A.Y.: Necessary and sufficient conditions for the uniform convergence of means to their expectations. Theory Probab. Appl. 26(3), 532–553 (1982) (Russian original: Теория вероятностеЙ и ее применения, 26(3), 543–564 (1981)) Vapnik, V.N., Chervonenkis, A.Y.: Necessary and sufficient conditions for the uniform convergence of means to their expectations. Theory Probab. Appl. 26(3), 532–553 (1982) (Russian original: Теория вероятностеЙ и ее применения, 26(3), 543–564 (1981))
6.
go back to reference Vapnik, V.N., Chervonenkis, A.Y.: Необходимые и достаточные условиясостоятельности метода минимизации эмпирического риска (Necessary and sufficient conditions for consistency of the method of empirical risk minimization, in Russian). In: Распознавание. Классификация. Прогноз (Recognition, Classification, and Forecasting), vol. 2, pp. 207–249. Nauka, Moscow (1989) Vapnik, V.N., Chervonenkis, A.Y.: Необходимые и достаточные условиясостоятельности метода минимизации эмпирического риска (Necessary and sufficient conditions for consistency of the method of empirical risk minimization, in Russian). In: Распознавание. Классификация. Прогноз (Recognition, Classification, and Forecasting), vol. 2, pp. 207–249. Nauka, Moscow (1989)
Metadata
Title
Measures of Complexity in the Theory of Machine Learning
Author
Alexey Chervonenkis
Copyright Year
2015
DOI
https://doi.org/10.1007/978-3-319-21852-6_13

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