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In this paper we study subsequences of random numbers. In Kamae (1973), selection functions that depend only on coordinates are studied, and their necessary and sufficient condition for the selected sequences to be normal numbers is given.…

Information Theory · Computer Science 2012-02-15 Hayato Takahashi

Inspired by Solomonoffs theory of inductive inference, we propose a prior based on circuit complexity. There are several advantages to this approach. First, it relies on a complexity measure that does not depend on the choice of UTM. There…

Machine Learning · Computer Science 2023-06-27 Cole Wyeth , Carl Sturtivant

First we consider pair-wise distances for literal objects consisting of finite binary files. These files are taken to contain all of their meaning, like genomes or books. The distances are based on compression of the objects concerned,…

Information Theory · Computer Science 2011-10-21 Paul M. B. Vitanyi

The concept of "logical depth" introduced by Charles H. Bennett (1988) seems to capture, at least partially, the notion of organized complexity, so central in big history. More precisely, the increase in organized complexity refers here to…

Other Computer Science · Computer Science 2018-05-16 Jean-Paul Delahaye , Clement Vidal

The main result is that: function descriptions are not made equal, and they can be categorised in at least two categories using various computational methods for function evaluation. The result affects Kolmogorov complexity and Random…

Computational Complexity · Computer Science 2020-03-12 Rade Vuckovac

The concept of overfitting in model selection is explained and demonstrated with an example. After providing some background information on information theory and Kolmogorov complexity, we provide a short explanation of Minimum Description…

Machine Learning · Computer Science 2010-05-17 Volker Nannen

We introduce a new mathematical framework for the probabilistic description of an experiment upon a system of any type in terms of initial information representing this system. Based on the notions of an information state, an information…

Quantum Physics · Physics 2007-05-23 Elena R. Loubenets

The notion of an individual random sequence goes back to von Mises. We describe the evolution of this notion, especially the use of martingales (suggested by Ville), and the development of algorithmic information theory in 1960s and 1970s…

History and Overview · Mathematics 2025-08-27 Laurent Bienvenu , Alexander Shen

Kolmogorov-Chaitin complexity has long been believed to be impossible to approximate when it comes to short sequences (e.g. of length 5-50). However, with the newly developed \emph{coding theorem method} the complexity of strings of length…

Computational Complexity · Computer Science 2015-02-23 Nicolas Gauvrit , Henrik Singmann , Fernando Soler-Toscano , Hector Zenil

Although information content is invariant up to an additive constant, the range of possible additive constants applicable to programming languages is so large that in practice it plays a major role in the actual evaluation of K(s), the…

Information Theory · Computer Science 2010-06-03 Jean-Paul Delahaye , Hector Zenil

This review presents recent and older results on elementary quantitative and qualitative aspects of consciousness and cognition and tackles the question "What is consciousness?" conjointly from biological, neuroscience-cognitive, physical…

Neurons and Cognition · Quantitative Biology 2018-07-17 Pierre Baudot

Quantum information brings together theories of physics and computer science. This synthesis challenges the basic intuitions of both fields. In this thesis, we show that adopting a unified and general language for process theories advances…

Quantum Physics · Physics 2015-12-29 William Zeng

Within psychology, neuroscience and artificial intelligence, there has been increasing interest in the proposal that the brain builds probabilistic models of sensory and linguistic input: that is, to infer a probabilistic model from a…

Machine Learning · Computer Science 2017-08-08 Paul M. B. Vitanyi , Nick Chater

This thesis details a class of partial orders on the space of probability distributions and the space of density operators which capture the idea of information content. Some links to domain theory and computational linguistics are also…

Logic in Computer Science · Computer Science 2017-01-25 John van de Wetering

The classical coding theorem in Kolmogorov complexity states that if an $n$-bit string $x$ is sampled with probability $\delta$ by an algorithm with prefix-free domain then K$(x) \leq \log(1/\delta) + O(1)$. In a recent work, Lu and…

Computational Complexity · Computer Science 2022-04-19 Zhenjian Lu , Igor C. Oliveira , Marius Zimand

The famous G\"odel incompleteness theorem states that for every consistent sufficiently rich formal theory T there exist true statements that are unprovable in T. Such statements would be natural candidates for being added as axioms, but…

The paper serves as the first contribution towards the development of the theory of efficiency: a unifying framework for the currently disjoint theories of information, complexity, communication and computation. Realizing the defining…

Computational Complexity · Computer Science 2016-10-26 Roman V. Yampolskiy

This expository paper advocates an approach to physics in which ``typicality" is identified with a suitable form of algorithmic randomness. To this end various theorems from mathematics and physics are reviewed. Their original versions…

Mathematical Physics · Physics 2023-09-06 Klaas Landsman

This work describes the principled design of a theoretical framework leading to fast and accurate algorithmic information measures on finite multisets of finite strings by means of compression. One distinctive feature of our approach is to…

Information Theory · Computer Science 2025-02-25 François Cayre

We investigate the information complexity of mixed-integer convex optimization under different types of oracles. We establish new lower bounds for the standard first-order oracle, improving upon the previous best known lower bound. This…

Optimization and Control · Mathematics 2023-08-23 Amitabh Basu , Hongyi Jiang , Phillip Kerger , Marco Molinaro