Non-algorithmic theory of randomness
Not on the map. Why?
Abstract (arXiv)
This paper proposes an alternative language for expressing results of the algorithmic theory of randomness. The language is more precise in that it does not involve unspecified additive or multiplicative constants, making mathematical results, in principle, applicable in practice. Our main testing ground for the proposed language is the problem of defining Bernoulli sequences, which was of great interest to Andrei Kolmogorov and his students.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 1 Oct 2019.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2025: 2.
2 papers.
- 2025Toward Universal Laws of Outlier Propagationcited by 3
- 2025Randomness, exchangeability, and conformal predictioncited by 1
- 2025Toward Universal Laws of Outlier Propagation12 Feb 2025
- 2025Randomness, exchangeability, and conformal prediction20 Jan 2025