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The definition of conditional probability in case of continuous distributions was an important step in the development of mathematical theory of probabilities. How can we define this notion in algorithmic probability theory? In this survey…

Logic · Mathematics 2016-07-15 Bruno Bauwens , Alexander Shen , Hayato Takahashi

Van Lambalgen's theorem states that a pair $(\alpha,\beta)$ of bitsequences is Martin-L\"of random if and only if $\alpha$ is Martin-L\"of random and $\beta$ is Martin-L\"of random relative to $\alpha$. In [Information and Computation 209.2…

Logic · Mathematics 2016-03-15 Bruno Bauwens

We generalise the randomness test definitions in the literature for both the Martin-L\"of and Schnorr randomness of a series of binary outcomes, in order to allow for interval-valued rather than merely precise forecasts for these outcomes,…

Probability · Mathematics 2023-12-21 Gert de Cooman , Floris Persiau , Jasper De Bock

We show that there exists a bitsequence that is not computably random for which its odd bits are computably random and its even bits are computably random relative to the odd bits. This implies that the uniform variant of van Lambalgen's…

Logic · Mathematics 2019-11-13 Bruno Bauwens

We extend some sharp inequalities for martingale-differences to general multiplicative systems of random variables. The key ingredient in the proofs is a technique reducing the general case to the case of Rademacher random variables without…

Classical Analysis and ODEs · Mathematics 2022-04-29 Grigori A. Karagulyan

The van Lambalgen theorem is a surprising result in algorithmic information theory concerning the symmetry of relative randomness. It establishes that for any pair of infinite sequences $A$ and $B$, $B$ is Martin-L\"of random and $A$ is…

Computational Complexity · Computer Science 2019-11-07 Diptarka Chakraborty , Satyadev Nandakumar , Himanshu Shukla

A concept of randomness for infinite time register machines (ITRMs), resembling Martin-L\"of-randomness, is defined and studied. In particular, we show that for this notion of randomness, computability from mutually random reals implies…

Logic · Mathematics 2026-05-19 Merlin Carl

As inductive inference and machine learning methods in computer science see continued success, researchers are aiming to describe ever more complex probabilistic models and inference algorithms. It is natural to ask whether there is a…

Logic · Mathematics 2019-11-19 Nathanael L. Ackerman , Cameron E. Freer , Daniel M. Roy

We study pairs of reals that are mutually Martin-L\"{o}f random with respect to a common, not necessarily computable probability measure. We show that a generalized version of van Lambalgen's Theorem holds for non-computable probability…

Logic · Mathematics 2016-02-10 Adam R. Day , Jan Reimann

This paper defines a new notion of bounded computable randomness for certain classes of sub-computable functions which lack a universal machine. In particular, we define such versions of randomness for primitive recursive functions and for…

Logic in Computer Science · Computer Science 2015-07-01 Sam Buss , Douglas Cenzer , Jeffrey B. Remmel

A concept of randomness for infinite time register machines (ITRMs) is defined and studied. In particular, we show that for this notion of randomness, computability from mutually random reals implies computability and that an analogue of…

Logic · Mathematics 2026-05-19 Merlin Carl

We correct Miyabe's proof of van Lambalgen's Theorem for truth-table Schnorr randomness (which we will call uniformly relative Schnorr randomness). An immediate corollary is one direction of van Lambalgen's theorem for Schnorr randomness.…

Logic · Mathematics 2013-05-02 Kenshi Miyabe , Jason Rute

We study algorithmic randomness and monotone complexity on product of the set of infinite binary sequences. We explore the following problems: monotone complexity on product space, Lambalgen's theorem for correlated probability,…

Information Theory · Computer Science 2010-06-29 Hayato Takahashi

The law of likelihood underlies a general framework, known as the likelihood paradigm, for representing and interpreting statistical evidence. As stated, the law applies only to simple hypotheses, and there have been reservations about…

Statistics Theory · Mathematics 2009-01-06 Zhiwei Zhang

We study Martin-L\"{o}f random (ML-random) points on computable probability measures on sample and parameter spaces (Bayes models). We consider variants of conditional randomness defined by ML-randomness on Bayes models and those of…

Information Theory · Computer Science 2023-04-24 Hayato Takahashi

We consider a randomised version of Kleene's realisability interpretation of intuitionistic arithmetic in which computability is replaced with randomised computability with positive probability. In particular, we show that (i) the set of…

Logic · Mathematics 2021-02-01 Merlin Carl , Lorenzo Galeotti , Robert Passmann

In algorithmic randomness, when one wants to define a randomness notion with respect to some non-computable measure $\lambda $, a choice needs to be made. One approach is to allow randomness tests to access the measure $\lambda $ as an…

Logic · Mathematics 2014-08-14 Bjørn Kjos-Hanssen , Antoine Taveneaux , Neil Thapen

We present the formalization of Doob's martingale convergence theorems in the mathlib library for the Lean theorem prover. These theorems give conditions under which (sub)martingales converge, almost everywhere or in $L^1$. In order to…

Logic in Computer Science · Computer Science 2022-12-13 Kexing Ying , Rémy Degenne

In this paper, we will generalize the definition of partially random or complex reals, and then show the duality of random and complex, i.e., a generalized version of Levin-Schnorr's theorem. We also study randomness from the view point of…

Logic · Mathematics 2017-04-05 Keita Yokoyama

We analyze selected iterated conditionals in the framework of conditional random quantities. We point out that it is instructive to examine Lewis's triviality result, which shows the conditions a conditional must satisfy for its probability…

Probability · Mathematics 2020-03-17 Giuseppe Sanfilippo , Angelo Gilio , David Over , Niki Pfeifer
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