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In the first part of this paper, we present a unified framework for analyzing the algorithmic complexity of any optimization problem, whether it be continuous or discrete in nature. This helps to formalize notions like "input", "size" and…

Optimization and Control · Mathematics 2022-07-06 Amitabh Basu

Specially customised Entropies are widely applied in measuring the degree of uncertainties existing in the frame of discernment. However, all of these entropies regard the frame as a whole that has already been determined which dose not…

Artificial Intelligence · Computer Science 2021-02-26 Yuanpeng He

The paper describes an approach to measuring convergence of an algorithm to its result in terms of an entropy-like function of partitions of its inputs of a given length. The goal is to look at the algorithmic data processing from the…

Computational Complexity · Computer Science 2016-05-06 Anatol Slissenko

The reduced density matrix of many-body systems possessing an additive conserved quantity can be decomposed in orthogonal sectors which can be independently analyzed. Recently, these have been proven to equally contribute to entanglement…

Statistical Mechanics · Physics 2020-08-05 Xhek Turkeshi , Paola Ruggiero , Vincenzo Alba , Pasquale Calabrese

A common meadow is an enrichment of a field with a partial division operation that is made total by assuming that division by zero takes the a default value, a special element $\bot$ adjoined to the field. To a common meadow of real numbers…

Information Theory · Computer Science 2025-02-12 Jan A Bergstra , John V Tucker

To extract essential information from complex data, computer scientists have been developing machine learning models that learn low-dimensional representation mode. From such advances in machine learning research, not only computer…

Artificial Intelligence · Computer Science 2024-06-18 Akira Matsui , Emilio Ferrara

We evaluated the impact of changing the observation scale over the entropy measures for text descriptions. MIDI coded Music, computer code and two human natural languages were studied at the scale of characters, words, and at the…

Information Theory · Computer Science 2017-01-13 Gerardo Febres , Klaus Jaffe

We show that there are infinitely many binary strings z, such that the sum of the on-line decision complexity of predicting the even bits of z given the previous uneven bits, and the decision complexity of predicting the uneven bits given…

Information Theory · Computer Science 2009-09-01 Bruno Bauwens

Infinite words, also known as streams, hold significant interest in computer science and mathematics, raising the natural question of how their complexity should be measured. We introduce cellular automaton reducibility as a measure of…

Formal Languages and Automata Theory · Computer Science 2026-01-30 Markel Zubia , Herman Geuvers

Background: Transitioning from an old medical coding system to a new one can be challenging, especially when the two coding systems are significantly different. The US experienced such a transition in 2015. Objective: This research aims to…

Information Theory · Computer Science 2020-12-24 Jerome Niyirora

Algorithmic statistics has two different (and almost orthogonal) motivations. From the philosophical point of view, it tries to formalize how the statistics works and why some statistical models are better than others. After this notion of…

Computational Complexity · Computer Science 2017-03-08 Nikolai Vereshchagin , Alexander Shen

The quantification of aleatoric and epistemic uncertainty in terms of conditional entropy and mutual information, respectively, has recently become quite common in machine learning. While the properties of these measures, which are rooted…

Machine Learning · Computer Science 2023-06-27 Lisa Wimmer , Yusuf Sale , Paul Hofman , Bern Bischl , Eyke Hüllermeier

The Gaussian width is a fundamental quantity in probability, statistics and geometry, known to underlie the intrinsic difficulty of estimation and hypothesis testing. In this work, we show how the Gaussian width, when localized to any given…

Statistics Theory · Mathematics 2018-03-22 Yuting Wei , Billy Fang , Martin J. Wainwright

During a spontaneous change, a macroscopic physical system will evolve towards a macro-state with more realizations. This observation is at the basis of the Statistical Mechanical version of the Second Law of Thermodynamics, and it provides…

Statistical Mechanics · Physics 2020-04-22 Mengjie Zu , Arunkumar Bupathy , Daan Frenkel , Srikanth Sastry

The multitime probability distributions obtained by repeatedly probing a quantum system via the measurement of an observable generally violate Kolmogorov's consistency property. Therefore, one cannot interpret such distributions as the…

In this study, the output of large language models (LLM) is considered an information source generating an unlimited sequence of symbols drawn from a finite alphabet. Given the probabilistic nature of modern LLMs, we assume a probabilistic…

Computation and Language · Computer Science 2026-02-24 Marco Scharringhausen

The normalized information distance is a universal distance measure for objects of all kinds. It is based on Kolmogorov complexity and thus uncomputable, but there are ways to utilize it. First, compression algorithms can be used to…

Information Retrieval · Computer Science 2008-09-16 Paul M. B. Vitanyi , Frank J. Balbach , Rudi L. Cilibrasi , Ming Li

So-called separation automata are in the core of several recently invented quasi-polynomial time algorithms for parity games. An explicit $q$-state separation automaton implies an algorithm for parity games with running time polynomial in…

Formal Languages and Automata Theory · Computer Science 2019-09-27 Alexander Kozachinskiy , Mikhail Vyalyi

Categorical compositional distributional model of Coecke et al. (2010) suggests a way to combine grammatical composition of the formal, type logical models with the corpus based, empirical word representations of distributional semantics.…

Computation and Language · Computer Science 2015-10-15 Esma Balkir , Mehrnoosh Sadrzadeh , Bob Coecke

Symmetry of information states that $C(x) + C(y|x) = C(x,y) + O(\log C(x))$. We show that a similar relation for online Kolmogorov complexity does not hold. Let the even (online Kolmogorov) complexity of an n-bitstring $x_1x_2... x_n$ be…

Information Theory · Computer Science 2014-01-09 Bruno Bauwens
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