English
Related papers

Related papers: Orders between channels and implications for parti…

200 papers

We present "PATRED", a technique that uses the addition of redundant information to facilitate the detection of specific, generally described patterns in line-charts during the visual exploration of the charts. We compared different…

Computation · Statistics 2022-05-30 Salomon Eisler , Joachim Meyer

Prediction polling is an increasingly popular form of crowdsourcing in which multiple participants estimate the probability or magnitude of some future event. These estimates are then aggregated into a single forecast. Historically,…

Methodology · Statistics 2016-04-25 Ville A. Satopää , Shane T. Jensen , Robin Pemantle , Lyle H. Ungar

A unified combinatorial definition of the information content and entropy of different types of patterns, compatible with the traditional concepts of information and entropy, going beyond the limitations of Shannon information interpretable…

Information Theory · Computer Science 2025-01-22 Zsolt Pocze

This paper studies problems of inferring order given noisy information. In these problems there is an unknown order (permutation) $\pi$ on $n$ elements denoted by $1,...,n$. We assume that information is generated in a way correlated with…

Data Structures and Algorithms · Computer Science 2009-10-08 Mark Braverman , Elchanan Mossel

In this paper, we take a unified approach for network information theory and prove a coding theorem, which can recover most of the achievability results in network information theory that are based on random coding. The final single-letter…

Information Theory · Computer Science 2015-05-22 Si-Hyeon Lee , Sae-Young Chung

Unsupervised learning plays an important role in many fields, such as artificial intelligence, machine learning, and neuroscience. Compared to static data, methods for extracting low-dimensional structure for dynamic data are lagging. We…

Machine Learning · Computer Science 2022-03-07 Rui Meng , Tianyi Luo , Kristofer Bouchard

Billey, Jockusch, and Stanley characterized 321-avoiding permutations by a property of their reduced decompositions. This paper generalizes that result with a detailed study of permutations via their reduced decompositions and the notion of…

Combinatorics · Mathematics 2007-05-23 Bridget Eileen Tenner

This paper presents a new foundational approach to information theory based on the concept of the information efficiency of a recursive function, which is defined as the difference between the information in the input and the output. The…

Information Theory · Computer Science 2023-08-29 Pieter Adriaans

Normalized information distance (NID) uses the theoretical notion of Kolmogorov complexity, which for practical purposes is approximated by the length of the compressed version of the file involved, using a real-world compression program.…

Computational Complexity · Computer Science 2009-10-23 Sebastiaan A. Terwijn , Leen Torenvliet , Paul M. B. Vitanyi

The logical basis for information theory is the newly developed logic of partitions that is dual to the usual Boolean logic of subsets. The key concept is a "distinction" of a partition, an ordered pair of elements in distinct blocks of the…

Information Theory · Computer Science 2013-01-29 David Ellerman

A major challenge in quantum communication is addressing the negative effects of noise on channel capacity, especially for completely depolarizing channels, where information transmission is inherently impossible. The concept of indefinite…

A growing interest in complex networks theory results in an ongoing demand for new analytical tools. We propose a novel measure based on information theory that provides a new perspective for a better understanding of networked systems:…

Neurons and Cognition · Quantitative Biology 2019-05-30 Aline Viol , Vesna Vuksanović , Philipp Hövel

Mutual information among three or more dimensions (mu-star = - Q) has been considered as interaction information. However, Krippendorff (2009a, 2009b) has shown that this measure cannot be interpreted as a unique property of the…

Information Retrieval · Computer Science 2010-01-08 Loet Leydesdorff

We propose a framework to analyze how multivariate representations disentangle ground-truth generative factors. A quantitative analysis of disentanglement has been based on metrics designed to compare how one variable explains each…

Machine Learning · Statistics 2022-02-11 Seiya Tokui , Issei Sato

Kolmogorov argued that the concept of information exists also in problems with no underlying stochastic model (as Shannon's information representation) for instance, the information contained in an algorithm or in the genome. He introduced…

Discrete Mathematics · Computer Science 2008-07-01 Joel Ratsaby

Physics-informed neural networks (PINNs) have been proposed to solve two main classes of problems: data-driven solutions and data-driven discovery of partial differential equations. This task becomes prohibitive when such data is highly…

Machine Learning · Computer Science 2022-10-20 Wei Peng , Wen Yao , Weien Zhou , Xiaoya Zhang , Weijie Yao

This technical note considers the problem of resource allocation in linear feedback control system with output disturbance. By decomposing the information rate in the feedback communication channel, the channel resource allocation is…

Information Theory · Computer Science 2015-11-12 Xue Dong , Kun Wang , Chong Xu , Weimin Wang

Objective: This work introduces a framework for multivariate time series analysis aimed at detecting and quantifying collective emerging behaviors in the dynamics of physiological networks. Methods: Given a network system mapped by a vector…

Applications · Statistics 2025-02-04 Luca Faes , Gorana Mijatovic , Laura Sparacino , Alberto Porta

In information theory, the link between continuous information and discrete information is established through well-known sampling theorems. Sampling theory explains, for example, how frequency-filtered music signals are reconstructible…

General Relativity and Quantum Cosmology · Physics 2009-11-10 Achim Kempf

In this paper, we introduce the proper latent decomposition (PLD) as a generalization of the proper orthogonal decomposition (POD) on manifolds. PLD is a nonlinear reduced-order modeling technique for compressing high-dimensional data into…

Machine Learning · Computer Science 2024-12-03 Daniel Kelshaw , Luca Magri