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Universal Probability-Free Conformal Prediction

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Book cover Conformal and Probabilistic Prediction with Applications (COPA 2016)

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Abstract

We construct a universal prediction system in the spirit of Popper’s falsifiability and Kolmogorov complexity. This prediction system does not depend on any statistical assumptions, but under the IID assumption it dominates, although in a rather weak sense, conformal prediction.

Not for nothing do we call the laws of nature “laws”: the more they prohibit, the more they say.

The Logic of Scientific Discovery

Karl Popper

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References

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  5. Shen, A.: Around Kolmogorov complexity: basic notions and results. In: Vovk, V., Papadopoulos, H., Gammerman, A. (eds.) Measures of Complexity: Festschrift for Alexey Chervonenkis, pp. 75–115. Springer, Cham (2015)

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  6. Vovk, V.: The basic conformal prediction framework. In: Balasubramanian, V.N., Ho, S.S., Vovk, V. (eds.) Conformal Prediction for Reliable Machine Learning: Theory, Adaptations, and Applications, chap. 1, pp. 3–19. Elsevier, Amsterdam (2014)

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Acknowledgments

We thank the anonymous referees for helpful comments. This work has been supported by the Air Force Office of Scientific Research (grant “Semantic Completions”), EPSRC (grant EP/K033344/1), and the EU Horizon 2020 Research and Innovation programme (grant 671555).

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Correspondence to Vladimir Vovk .

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© 2016 Springer International Publishing Switzerland

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Vovk, V., Pavlovic, D. (2016). Universal Probability-Free Conformal Prediction. In: Gammerman, A., Luo, Z., Vega, J., Vovk, V. (eds) Conformal and Probabilistic Prediction with Applications. COPA 2016. Lecture Notes in Computer Science(), vol 9653. Springer, Cham. https://doi.org/10.1007/978-3-319-33395-3_3

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  • DOI: https://doi.org/10.1007/978-3-319-33395-3_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-33394-6

  • Online ISBN: 978-3-319-33395-3

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