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The hypothesis of randomness is fundamental in statistical machine learning and in many areas of nonparametric statistics; it says that the observations are assumed to be independent and coming from the same unknown probability distribution.
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Richard von Mises · 1919
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Economic Control of Quality of Manufactured Product
Walter A. Shewhart · 1931
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Etude critique de la notion de collectif
Jean Ville · 1939
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An exact test for randomness in the non-parametric case based on serial correlation
Abraham Wald and Jacob Wolfowitz · 1943
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Sequential tests of statistical hypotheses
Abraham Wald · 1945
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Sequential Analysis
Abraham Wald · 1947
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Optimum character of the sequential probability ratio test
Abraham Wald and Jacob Wolfowitz · 1948
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Andrei N. Kolmogorov · 1950
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Stochastic Processes
Joseph L. Doob · 1953
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Continuous inspection schemes
Ewan S. Page · 1954
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A remark on Stirling’s formula
Herbert Robbins · 1955
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A new interpretation of information rate
John L. Kelly · 1956
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Andrei N. Kolmogorov and Albert N. Shiryaev · 1960
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Harold Jeffreys · 1961
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Andrei N. Kolmogorov · 1963
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On optimum methods in quickest detection problems
Albert N. Shiryaev · 1963
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Per Martin-Löf · 1966
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S. W. Roberts · 1966
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Logical basis for information theory and probability theory
Andrei N. Kolmogorov · 1968
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Nonparametrics: Statistical Methods Based on Ranks
Erich L. Lehmann · 1975
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Karl R. Popper · 1982
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