Complexity Approximation Principle
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[1] Vladimir Vovk,et al. Probability theory for the Brier game , 1997, Theor. Comput. Sci..
[2] A. Kolmogorov. Three approaches to the quantitative definition of information , 1968 .
[3] Ming Li,et al. Kolmogorov Complexity and its Applications , 1991, Handbook of Theoretical Computer Science, Volume A: Algorithms and Complexity.
[4] David Haussler,et al. Tight worst-case loss bounds for predicting with expert advice , 1994, EuroCOLT.
[5] J. Rissanen. A UNIVERSAL PRIOR FOR INTEGERS AND ESTIMATION BY MINIMUM DESCRIPTION LENGTH , 1983 .
[6] Erik Ordentlich,et al. Universal portfolios with side information , 1996, IEEE Trans. Inf. Theory.
[7] Vladimir V. V'yugin,et al. Algorithmic Complexity and Stochastic Properties of Finite Binary Sequences , 1999, Comput. J..
[8] J. Lewins. Contribution to the Discussion , 1989 .
[9] Vladimir Vovk,et al. Aggregating strategies , 1990, COLT '90.
[10] Jorma Rissanen,et al. Hypothesis Selection and Testing by the MDL Principle , 1999, Comput. J..
[11] C. Q. Lee,et al. The Computer Journal , 1958, Nature.
[12] Vladimir Vovk,et al. A game of prediction with expert advice , 1995, COLT '95.
[13] Alexander Gammerman,et al. Kolmogorov Complexity: Sources, Theory and Applications , 1999, Comput. J..
[14] Vladimir Vapnik,et al. Statistical learning theory , 1998 .
[15] Vladimir Vovk,et al. Universal portfolio selection , 1998, COLT' 98.
[16] Ming Li,et al. An Introduction to Kolmogorov Complexity and Its Applications , 2019, Texts in Computer Science.
[17] L. Levin,et al. THE COMPLEXITY OF FINITE OBJECTS AND THE DEVELOPMENT OF THE CONCEPTS OF INFORMATION AND RANDOMNESS BY MEANS OF THE THEORY OF ALGORITHMS , 1970 .
[18] C. S. Wallace,et al. Estimation and Inference by Compact Coding , 1987 .