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Many types of pairwise interaction take the form of a fixed set of nodes with edges that appear and disappear over time. In the case of discrete-time evolution, the resulting evolving network may be represented by a time-ordered sequence of…

Social and Information Networks · Computer Science 2019-04-10 Caterina Fenu , Desmond J. Higham

Hierarchical clustering of networks consists in finding a tree of communities, such that lower levels of the hierarchy reveal finer-grained community structures. There are two main classes of algorithms tackling this problem. Divisive…

Social and Information Networks · Computer Science 2025-11-25 Maximilien Dreveton , Daichi Kuroda , Matthias Grossglauser , Patrick Thiran

We investigate the problem of "nonlocal" computation, in which separated parties must compute a function with nonlocally encoded inputs and output, such that each party individually learns nothing, yet together they compute the correct…

Quantum Physics · Physics 2017-08-01 Noah Linden , Sandu Popescu , Anthony J. Short , Andreas Winter

The paper develops a general framework for constrained clustering which is based on the close connection of geometric clustering and diagrams. Various new structural and algorithmic results are proved (and known results generalized and…

Data Structures and Algorithms · Computer Science 2017-04-10 Andreas Brieden , Peter Gritzmann , Fabian Klemm

Restriction categories provide a categorical framework for partiality. In this paper, we introduce three new categorical theories for partiality: local categories, partial categories, and inclusion categories. The objects of a local…

Category Theory · Mathematics 2025-12-04 Marcello Lanfranchi , Jean-Simon Pacaud Lemay

We present a method for optimizing quantum circuits architecture. The method is based on the notion of "quantum comb", which describes a circuit board in which one can insert variable subcircuits. The method allows one to efficiently…

Quantum Physics · Physics 2008-09-08 Giulio Chiribella , Giacomo Mauro D'Ariano , Paolo Perinotti

Network science has presented community detection as a valuable tool for revealing functional modules in complex systems rooted in the wiring architectures of complex networks. The varying procedures of community detection can produce,…

Physics and Society · Physics 2025-04-11 Karsten N. Economou , Cassie R. Norman , Wendy C. Gentleman

Community structures detection in complex network is important for understanding not only the topological structures of the network, but also the functions of it. Stochastic block model and nonnegative matrix factorization are two widely…

Social and Information Networks · Computer Science 2017-07-11 Zhong-Yuan Zhang , Yujie Gai , Yu-Fei Wang , Hui-Min Cheng , Xin Liu

The symplectic blob algebra is a physically motivated quotient of the Hecke algebra $H(\tilde{C}_n)$ with a diagram calculus. We find the blocks for the symplectic blob algebra for all specialisations of its parameters over the complex…

Representation Theory · Mathematics 2024-07-11 Oliver H. King , Paul P. Martin , Alison E. Parker

A neighborhood homotopy is an equivalence relation on spatial graphs which is generated by crossing changes on the same component and neighborhood equivalence. We give a complete classification of all 2-component spatial graphs up to…

Geometric Topology · Mathematics 2020-05-19 Atsuhiko Mizusawa , Ryo Nikkuni

Stochastic blockmodels have been proposed as a tool for detecting community structure in networks as well as for generating synthetic networks for use as benchmarks. Most blockmodels, however, ignore variation in vertex degree, making them…

Physics and Society · Physics 2011-03-02 Brian Karrer , M. E. J. Newman

The paper describes clustering problems from the combinatorial viewpoint. A brief systemic survey is presented including the following: (i) basic clustering problems (e.g., classification, clustering, sorting, clustering with an order over…

Artificial Intelligence · Computer Science 2015-06-01 Mark Sh. Levin

The computational efficiency of quantum mechanics can be defined in terms of the qubit circuit model, which is characterized by a few simple properties: each computational gate is a reversible transformation in a connected matrix group;…

Quantum Physics · Physics 2019-01-30 Marius Krumm , Markus P. Mueller

There is a construction which lies at the heart of descent theory. The combinatorial aspects of this paper concern the description of the construction in all dimensions. The description is achieved precisely for strict n-categories and…

Category Theory · Mathematics 2007-05-23 Ross Street

Classification is an important goal in many branches of mathematics. The idea is to describe the members of some class of mathematical objects, up to isomorphism or other important equivalence in terms of relatively simple invariants. Where…

Logic · Mathematics 2008-03-25 Wesley Calvert , Julia F. Knight

Cyclicity of a convolutional code (CC) is relying on a nontrivial automorphism of the algebra F[x]/(x^n-1), where F is a finite field. If this automorphism itself has certain specific cyclicity properties one is lead to the class of…

Rings and Algebras · Mathematics 2007-07-16 Heide Gluesing-Luerssen , Wiland Schmale

This work proposes a hierarchical clustering algorithm for high-dimensional datasets using the cyclic space of reversible finite cellular automata. In cellular automaton (CA) based clustering, if two objects belong to the same cycle, they…

Formal Languages and Automata Theory · Computer Science 2024-08-06 Baby C. J. , Kamalika Bhattacharjee

A composition of a nonnegative integer (n) is a sequence of positive integers whose sum is (n). A composition is palindromic if it is unchanged when its terms are read in reverse order. We provide a generating function for the number of…

Combinatorics · Mathematics 2007-05-23 Sergey Kitaev , Tyrrell B. McAllister , T. Kyle Petersen

This paper describes a new approach for learning structures of large Bayesian networks based on blocks resulting from feature space clustering. This clustering is obtained using normalized mutual information. And the subsequent aggregation…

Machine Learning · Statistics 2022-08-30 Anna V. Bubnova

Clustering is often a challenging problem because of the inherent ambiguity in what the "correct" clustering should be. Even when the number of clusters $K$ is known, this ambiguity often still exists, particularly when there is variation…

Information Theory · Computer Science 2025-05-09 Kayvon Mazooji , Ilan Shomorony