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Erschienen in: Automatic Documentation and Mathematical Linguistics 2/2022

01.04.2022 | GENERAL SECTION

Loss of Scientific Knowledge As a Consequence of Publication Requirements

verfasst von: D. V. Vinogradov

Erschienen in: Automatic Documentation and Mathematical Linguistics | Ausgabe 2/2022

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Abstract

In the process of analyzing modern courses on Bayesian methods in machine learning, we discovered there to be a loss of knowledge on the inconsistency of Bayesian learning of the Dirichlet model. We present a particularly simple presentation of such a failure. The reason for the phenomenon of forgetting known scientific facts is a change in the requirements for publications in scientific journals, i.e., references only to modern publications (not older than 5 years).
Literatur
1.
Zurück zum Zitat Bishop, C.M., Pattern Recognition and Machine Learning, Information Science and Statistics, New York: Springer, 2006. Bishop, C.M., Pattern Recognition and Machine Learning, Information Science and Statistics, New York: Springer, 2006.
3.
Zurück zum Zitat Miller, J.W. and Harrison, M.T., A simple example of Dirichlet process mixture inconsistency for the number of components, Proc. 26th Int. Conf. on Neural Information Processing Systems, Lake Tahoe, Nev., 2013, Burges, C.J.C., Bottou, L., Welling, M., Ghahramani, Z., and Weinberger, K.Q., Eds., Red Hook, N.Y.: Curran Associates, 2013, vol. 1, pp. 199–206. Miller, J.W. and Harrison, M.T., A simple example of Dirichlet process mixture inconsistency for the number of components, Proc. 26th Int. Conf. on Neural Information Processing Systems, Lake Tahoe, Nev., 2013, Burges, C.J.C., Bottou, L., Welling, M., Ghahramani, Z., and Weinberger, K.Q., Eds., Red Hook, N.Y.: Curran Associates, 2013, vol. 1, pp. 199–206.
Metadaten
Titel
Loss of Scientific Knowledge As a Consequence of Publication Requirements
verfasst von
D. V. Vinogradov
Publikationsdatum
01.04.2022
Verlag
Pleiades Publishing
Erschienen in
Automatic Documentation and Mathematical Linguistics / Ausgabe 2/2022
Print ISSN: 0005-1055
Elektronische ISSN: 1934-8371
DOI
https://doi.org/10.3103/S0005105522020078

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