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A family of parsimonious shifted asymmetric Laplace mixture models is introduced. We extend the mixture of factor analyzers model to the shifted asymmetric Laplace distribution. Imposing constraints on the constitute parts of the resulting…

Methodology · Statistics 2013-11-05 Brian C. Franczak , Paul D. McNicholas , Ryan P. Browne , Paula M. Murray

Numerical simulation of lattice gauge theories is an indispensable tool in high energy physics, and their quantum simulation is expected to become a major application of quantum computers in the future. In this work, for an Abelian lattice…

Quantum Physics · Physics 2023-05-24 Hiroki Sukeno , Takuya Okuda

We compare the different convergence criteria available for cluster expansions of polymer gases subjected to hard-core exclusions, with emphasis on polymers defined as finite subsets of a countable set (e.g. contour expansions and more…

Mathematical Physics · Physics 2015-05-18 Rodrigo Bissacot , Roberto Fernández , Aldo Procacci

We present a principled spectral approach to the well-studied constrained clustering problem. It reduces clustering to a generalized eigenvalue problem on Laplacians. The method works in nearly-linear time and provides concrete guarantees…

Social and Information Networks · Computer Science 2016-01-20 Mihai Cucuringu , Ioannis Koutis , Sanjay Chawla

Using the character expansion method, we generalize several well-known integrals over the unitary group to the case where general complex matrices appear in the integrand. These integrals are of interest in the theory of random matrices and…

Mathematical Physics · Physics 2008-11-26 B. Schlittgen , T. Wettig

Percolation refers to an interesting class of problems related to the properties of disordered systems, usually formulated in terms of objects randomly placed on an underlying lattice or continuum. Despite the simplicity of the setup, most…

Statistical Mechanics · Physics 2022-02-22 Abraham Levitan

Observational data usually comes with a multimodal nature, which means that it can be naturally represented by a multi-layer graph whose layers share the same set of vertices (users) with different edges (pairwise relationships). In this…

Machine Learning · Computer Science 2015-08-31 Xiaowen Dong , Pascal Frossard , Pierre Vandergheynst , Nikolai Nefedov

The area of constrained clustering has been extensively explored by researchers and used by practitioners. Constrained clustering formulations exist for popular algorithms such as k-means, mixture models, and spectral clustering but have…

Machine Learning · Computer Science 2019-12-20 Hongjing Zhang , Sugato Basu , Ian Davidson

The article contains a preliminary glance at balanced clustering problems. Basic balanced structures and combinatorial balanced problems are briefly described. A special attention is targeted to various balance/unbalance indices (including…

Data Structures and Algorithms · Computer Science 2017-06-13 Mark Sh. Levin

The model with the fermions coupled in the non - minimal way to the gauge theory of Lorentz group is considered. The lattice regularization is suggested. It is argued that this model may exist in the phase with broken chiral symmetry and…

High Energy Physics - Lattice · Physics 2013-08-16 M. A. Zubkov

A binary lattice gas model that allows for multiple occupancy of lattice sites, inspired by recent coarse-grained descriptions of solutions of interacting polymers, is investigated by combining the steepest descent approximation with an…

Soft Condensed Matter · Physics 2007-05-23 Reimar Finken , Jean-Pierre Hansen , Ard Louis

The coupled (chaotic) map lattices (CMLs) characterizes the collective dynamics of a spatially distributed system consisting of locally or globally coupled maps. The current research on the dynamic behavior of CMLs is based on the framework…

Dynamical Systems · Mathematics 2025-07-22 Junke Zhang , Yiqian Wang

Reconstruction based subspace clustering methods compute a self reconstruction matrix over the samples and use it for spectral clustering to obtain the final clustering result. Their success largely relies on the assumption that the…

Machine Learning · Computer Science 2012-06-22 Ruijiang Li , Bin Li , Ke Zhang , Cheng Jin , Xiangyang Xue

We study supervised learning problems using clustering constraints to impose structure on either features or samples, seeking to help both prediction and interpretation. The problem of clustering features arises naturally in text…

Machine Learning · Computer Science 2016-09-20 Vincent Roulet , Fajwel Fogel , Alexandre d'Aspremont , Francis Bach

The tensor renormalization group is a promising complementary approach to traditional Monte Carlo methods for lattice systems, as it is inherently free from the sign problem. We discuss recent developments crucial for its application to…

High Energy Physics - Lattice · Physics 2025-01-27 Atis Yosprakob

In this paper, we prove some combinatorial results on generalized cluster algebras. To be more precisely, we prove that (i) the seeds of a generalized cluster algebra $\mathcal A(\mathcal S)$ whose clusters contain particular cluster…

Rings and Algebras · Mathematics 2019-10-09 Peigen Cao , Fang Li

We use an extension of fundamental measure theory to lattice hard-core fluids to study the phase diagram of two different systems. First, two-dimensional parallel hard squares with edge-length $\sigma=2$ in a simple square lattice. This…

Soft Condensed Matter · Physics 2009-11-10 Luis Lafuente , Jose A. Cuesta

A mixture of shifted asymmetric Laplace distributions is introduced and used for clustering and classification. A variant of the EM algorithm is developed for parameter estimation by exploiting the relationship with the general inverse…

Methodology · Statistics 2017-10-09 Brian C. Franczak , Ryan P. Browne , Paul D. McNicholas

Growth mixture models are an important tool for detecting group structure in repeated measures data. Unlike traditional clustering methods, they explicitly model the repeat measurements on observations, and the statistical framework they…

Methodology · Statistics 2017-10-20 Abby Flynt , Nema Dean

One of the fundamental problems in network analysis is detecting community structure in multi-layer networks, of which each layer represents one type of edge information among the nodes. We propose integrative spectral clustering approaches…

Machine Learning · Statistics 2022-10-07 Sihan Huang , Haolei Weng , Yang Feng