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In this work, we tackle the problem of hidden community detection. We consider Belief Propagation (BP) applied to the problem of detecting a hidden Erd\H{o}s-R\'enyi (ER) graph embedded in a larger and sparser ER graph, in the presence of…

Machine Learning · Computer Science 2017-03-07 Arun Kadavankandy , Konstantin Avrachenkov , Laura Cottatellucci , Rajesh Sundaresan

In the context of solving large distributed constraint optimization problems (DCOP), belief-propagation and approximate inference algorithms are candidates of choice. However, in general, when the factor graph is very loopy (i.e. cyclic),…

Multiagent Systems · Computer Science 2017-06-08 Jesús Cerquides , Rémi Emonet , Gauthier Picard , Juan A. Rodríguez-Aguilar

We consider the Degree-Corrected Stochastic Block Model (DC-SBM): a random graph on $n$ nodes, having i.i.d. weights $(\phi_u)_{u=1}^n$ (possibly heavy-tailed), partitioned into $q \geq 2$ asymptotically equal-sized clusters. The model…

Probability · Mathematics 2018-11-27 Lennart Gulikers , Marc Lelarge , Laurent Massoulié

Goulden and Jackson (1996) introduced, using Jack symmetric functions, some multivariate generating series $\psi(x, y, z; t, 1+\beta)$ that might be interpreted as a continuous deformation of the generating series of rooted hypermaps. They…

Combinatorics · Mathematics 2017-10-16 Maciej Dołęga , Valentin Féray

We introduce the balanced crown decomposition that captures the structure imposed on graphs by their connected induced subgraphs of a given size. Such subgraphs are a popular modeling tool in various application areas, where the non-local…

Data Structures and Algorithms · Computer Science 2021-06-25 Katrin Casel , Tobias Friedrich , Davis Issac , Aikaterini Niklanovits , Ziena Zeif

Belief propagation (BP) is a useful probabilistic inference algorithm for efficiently computing approximate marginal probability densities of random variables. However, in its standard form, BP is only applicable to the vector-type random…

Artificial Intelligence · Computer Science 2024-04-05 Hyowon Kim , Angel F. García-Fernández , Yu Ge , Yuxuan Xia , Lennart Svensson , Henk Wymeersch

Sampling-based algorithms are classical approaches to perform Bayesian inference in inverse problems. They provide estimators with the associated credibility intervals to quantify the uncertainty on the estimators. Although these methods…

Methodology · Statistics 2023-11-28 Pierre-Antoine Thouvenin , Audrey Repetti , Pierre Chainais

The name graph state is used to describe a certain class of pure quantum state which models a physical structure on which one can perform measurement-based quantum computing, and which has a natural graphical description. We present the…

Quantum Physics · Physics 2008-01-31 Constanza Riera , Stephane Jacob , Matthew G. Parker

A \emph{palindrome} is a word that reads the same forwards and backwards. A \emph{block palindrome factorization} (or \emph{BP-factorization}) is a factorization of a word into blocks that becomes palindrome if each identical block is…

Combinatorics · Mathematics 2023-04-17 Daniel Gabric , Jeffrey Shallit

Quantum error correction (QEC) is critical for scalable fault-tolerant quantum computing. Topological codes, such as the toric code, offer hardware-efficient architectures but their Tanner graphs contain many girth-4 cycles that degrade the…

Quantum Physics · Physics 2026-03-24 Luca Menti , Francisco Lázaro

In this manuscript a factor graph approach is employed to investigate the recursive filtering problem for a mixed linear/nonlinear state-space model, i.e. for a model whose state vector can be partitioned in a linear state variable…

Statistics Theory · Mathematics 2016-07-29 Giorgio M. Vitetta , Emilio Sirignano , Francesco Montorsi , Matteo Sola

We introduce a novel quantum algorithm for determining graph connectedness using a constant number of measurements. The algorithm can be extended to find connected components with a linear number of measurements. It relies on non-unitary…

Quantum Physics · Physics 2024-12-05 Maximilian Balthasar Mansky , Chonfai Kam , Claudia Linnhoff-Popien

We describe a method for parameter estimation in bipartite probabilistic graphical models for joint prediction of clinical conditions from the electronic medical record. The method does not rely on the availability of gold-standard labels,…

Machine Learning · Statistics 2016-09-23 Yoni Halpern , Steven Horng , David Sontag

Bibliographic coupling (BC) and co-citation (CC) are the two most common citation-based coupling measures of similarity between scientific items. One can interpret these measures as second-neighbor relations distinguished by the direction…

Physics and Society · Physics 2021-11-01 Jinhyuk Yun

Simulation-based calibration checking (SBC) is a practical method to validate computationally-derived posterior distributions or their approximations. In this paper, we introduce a new variant of SBC to alleviate several known problems. Our…

We consider bivariate polynomials over the skew field of quaternions, where the indeterminates commute with all coefficients and with each other. We analyze existence of univariate factorizations, that is, factorizations with univariate…

Rings and Algebras · Mathematics 2021-11-08 Johanna Lercher , Hans-Peter Schröcker

We address the problem of partitioning a vertex-weighted connected graph into $k$ connected subgraphs that have similar weights, for a fixed integer $k\geq 2$. This problem, known as the \emph{balanced connected $k$-partition problem}…

Discrete Mathematics · Computer Science 2019-11-14 Flávio K. Miyazawa , Phablo F. S. Moura , Matheus J. Ota , Yoshiko Wakabayashi

Product constructions constitute a powerful method for generating quantum CSS codes, yielding celebrated examples such as toric codes and asymptotically good low-density parity check (LDPC) codes. Since a CSS code is fully described by a…

Quantum Physics · Physics 2026-02-02 Meng-Yuan Li

Symbolic regression that aims to detect underlying data-driven models has become increasingly important for industrial data analysis. For most existing algorithms such as genetic programming (GP), the convergence speed might be too slow for…

Neural and Evolutionary Computing · Computer Science 2017-10-31 Chen Chen , Changtong Luo , Zonglin Jiang

The framework of statistical inference has been successfully used to detect the meso-scale structures in complex networks, such as community structure, core-periphery (CP) structure. The main principle is that the stochastic block model…

Physics and Society · Physics 2018-08-29 Chuang Ma , Bing-Bing Xiang , Han-Shuang Chen , Hai-Feng Zhang