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Representing patterns as labeled graphs is becoming increasingly common in the broad field of computational intelligence. Accordingly, a wide repertoire of pattern recognition tools, such as classifiers and knowledge discovery procedures,…

Computer Vision and Pattern Recognition · Computer Science 2017-05-11 Lorenzo Livi

Hypergraphs are an invaluable tool to understand many hidden patterns in large data sets. Among many ways to represent hypergraph, one useful representation is that of weighted clique expansion. In this paper, we consider this…

Combinatorics · Mathematics 2018-08-15 Ashwin Guha , Ambedkar Dukkipati

We define notions of local topological convergence and local geometric convergence for embedded graphs in $\mathbb{R}^n,$ and study their properties. The former is related to Benjamini-Schramm convergence, and the latter to weak convergence…

Probability · Mathematics 2017-06-28 Benjamin Schweinhart

In this paper the problem of finding various spanning structures in random hypergraphs is studied. We notice that a general result of Riordan [Spanning subgraphs of random graphs, Combinatorics, Probability & Computing 9 (2000), no. 2,…

Combinatorics · Mathematics 2015-04-13 Olaf Parczyk , Yury Person

Let $H_n$ be a graph on $n$ vertices and let $\ber{H_n}$ denote the complement of $H_n$. Suppose that $\Delta = \Delta(n)$ is the maximum degree of $\ber{H_n}$. We analyse three algorithms for sampling $d$-regular subgraphs ($d$-factors) of…

Combinatorics · Mathematics 2019-10-25 Pu Gao , Catherine Greenhill

We compute the entanglement entropy in a composite system separated by a finitely ramified boundary with the structure of a self-similar lattice graph. We derive the entropy as a function of the decimation factor which determines the…

Quantum Physics · Physics 2018-11-14 Ibrahim Akal

We quantify a social organization's potentiality, that is its ability to attain different configurations. The organization is represented as a network in which nodes correspond to individuals and (multi-)edges to their multiple…

Physics and Society · Physics 2019-09-18 Christian Zingg , Giona Casiraghi , Giacomo Vaccario , Frank Schweitzer

We show how universal codes can be used for solving some of the most important statistical problems for time series. By definition, a universal code (or a universal lossless data compressor) can compress any sequence generated by a…

Information Theory · Computer Science 2008-09-09 Boris Ryabko

We propose a universal approach to a range of enumeration problems in graphs. The key point is in contracting suitably chosen symmetric tensors placed at the vertices of a graph along the edges. In particular, this leads to an algorithm…

Combinatorics · Mathematics 2007-05-23 Peter Zograf

We consider the problem of automatically decomposing operations over tensors or arrays so that they can be executed in parallel on multiple devices. We address two, closely-linked questions. First, what programming abstraction should…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-10-04 Daniel Bourgeois , Zhimin Ding , Dimitrije Jankov , Jiehui Li , Mahmoud Sleem , Yuxin Tang , Jiawen Yao , Xinyu Yao , Chris Jermaine

For any graph, we define a rank-1 operator on a bipartite tensor product space, with components associated to the set of vertices and edges respectively. We show that the partial traces of the operator are the Laplacian and the…

Combinatorics · Mathematics 2013-05-01 Niel de Beaudrap , Vittorio Giovannetti , Simone Severini , Richard Wilson

A new conceptual foundation for the notion of "information" is proposed, based on the concept of a "distinction graph": a graph in which two nodes are connected iff they cannot be distinguished by a particular observer. The "graphtropy" of…

Artificial Intelligence · Computer Science 2019-02-05 Ben Goertzel

Shannon entropy is widely used to quantify the uncertainty of discrete random variables. But when normalized to the unit interval, as is often done in practice, it no longer conveys the alphabet sizes of the random variables being studied.…

Information Theory · Computer Science 2022-07-26 John Çamkıran

We analyze entropic uncertainty relations for two orthogonal measurements on a $N$-dimensional Hilbert space, performed in two generic bases. It is assumed that the unitary matrix $U$ relating both bases is distributed according to the Haar…

Quantum Physics · Physics 2016-08-10 Radosław Adamczak , Rafał Latała , Zbigniew Puchała , Karol Życzkowski

In arXiv:1310.5713 and arXiv:1310.6659 a formula was proposed as the entanglement entropy functional for a general higher-derivative theory of gravity, whose lagrangian consists of terms containing contractions of the Riemann tensor. In…

High Energy Physics - Theory · Physics 2015-02-24 Arpan Bhattacharyya , Menika Sharma

In this note a notion of generalized topological entropy for arbitrary subsets of the space of all sequences in a compact topological space is introduced. It is shown that for a continuous map on a compact space the generalized topological…

Dynamical Systems · Mathematics 2024-10-29 Maysam Maysami Sadr , Mina Shahrestani

Isomorph theory is one of the promising theories to understand the quasi-universal relationship between thermodynamic, dynamic and structural characteristics. Based on the hidden scale invariance of the inverse power law potentials, it…

Statistical Mechanics · Physics 2019-07-31 Tae Jun Yoon , Min Young Ha , Emanuel A. Lazar , Won Bo Lee , Youn-Woo Lee

We introduce a simple geometrical construction similar to covariant holographic entanglement entropy but with the addition of a new term proportional to boundary region volume. This new procedure has properties strongly resembling classical…

High Energy Physics - Theory · Physics 2019-05-10 Sean J. Weinberg

On a compact group the Haar probability measure plays the role of uniform distribution. The entropy and rate distortion theory for this uniform distribution is studied. New results and simplified proofs on convergence of convolutions on…

Information Theory · Computer Science 2010-05-27 Peter Harremoes

In the online prediction framework, we use generalized entropy of to study the loss rate of predictors when outcomes are drawn according to stationary ergodic distributions over the binary alphabet. We show that the notion of generalized…

Information Theory · Computer Science 2016-03-08 Mrinalkanti Ghosh , Satyadev Nandakumar
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