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We present a methodology that extends invariant manifold theory to a class of autonomous piecewise linear systems with nonsmoothness at the equilibrium, providing a framework for model order reduction in mechanical structures with compliant…

Dynamical Systems · Mathematics 2026-01-16 A. Yassine Karoui , Remco I. Leine

Estimating copulas with discrete marginal distributions is challenging, especially in high dimensions, because computing the likelihood contribution of each observation requires evaluating $2^{J}$ terms, with $J$ the number of discrete…

Methodology · Statistics 2018-11-12 D. Gunawan , M. -N. Tran , K. Suzuki , J. Dick , R. Kohn

This paper gives two different proofs to a structural theorem of decreasing minimization (lexicographic optimization) on integrally convex sets. The theorem states that the set of decreasingly minimal elements of an integrally convex set…

Optimization and Control · Mathematics 2025-04-28 Kazuo Murota , Akihisa Tamura

We introduce the coverage correlation coefficient, a novel nonparametric measure of statistical association designed to quantifies the extent to which two random variables have a joint distribution concentrated on a singular subset with…

Methodology · Statistics 2025-08-18 Xuzhi Yang , Mona Azadkia , Tengyao Wang

In this paper we introduce and experimentally compare alternative algorithms to join uncertain relations. Different algorithms are based on specific principles, e.g., sorting, indexing, or building intermediate relational tables to apply…

Databases · Computer Science 2012-11-02 Matteo Magnani , Danilo Montesi

Comparative judgement studies elicit quality assessments through pairwise comparisons, typically analysed using the Bradley-Terry model. A challenge in these studies is experimental design, specifically, determining the optimal pairs to…

Methodology · Statistics 2026-03-24 Jiahua Jiang , Joseph Marsh , Rowland G Seymour

In theory, the probabilistic linkage method provides two distinct advantages over non-probabilistic methods, including minimal rates of linkage error and accurate measures of these rates for data users. However, implementations can fall…

Methodology · Statistics 2019-11-06 Abel Dasylva , Arthur Goussanou , David Ajavon , Hanan Abousaleh

We investigate creation of optimal entanglement in symmetric networks. The proposed network is one in which the connections are organized by a group table in other words a group association scheme. We show that optimal entanglement can be…

Quantum Physics · Physics 2009-09-10 M. Ghojavand , M. A. Jafarizadeh , S. Rouhani

Inverse methods of statistical mechanics have facilitated the discovery of pair potentials that stabilize a wide variety of targeted lattices at zero temperature. However, such methods are complicated by the need to compare, within the…

Statistical Mechanics · Physics 2016-09-19 Beth A. Lindquist , Ryan B. Jadrich , Thomas M. Truskett

In this work we consider two models of two dimensional discrete systems subjected to three different types of coupling and analyse systematically the performance of each in realising synchronised states.We find that linear coupling…

Chaotic Dynamics · Physics 2009-11-11 G Ambika , K Ambika

Using methods of statistical physics, we analyse the error of learning couplings in large Ising models from independent data (the inverse Ising problem). We concentrate on learning based on local cost functions, such as the…

Disordered Systems and Neural Networks · Physics 2017-08-02 Ludovica Bachschmid-Romano , Manfred Opper

The joint distribution $P(X,Y)$ cannot be determined from its marginals $P(X)$ and $P(Y)$ alone; one also needs one of the conditionals $P(X|Y)$ or $P(Y|X)$. But is there a best guess, given only the marginals? Here we answer this question…

Statistics Theory · Mathematics 2020-05-26 Richard Rohwer

This paper investigates the use of the most fundamental elements; cables for tension and bars for compression, in the search for the most efficient bridges. Stable arrangements of these elements are called tensegrity structures. We show…

Materials Science · Physics 2014-12-18 Gerardo Carpentieri , Robert E. Skelton , Fernando Fraternali

This paper studies distributed convex optimization with both affine equality and nonlinear inequality couplings through the duality analysis. We first formulate the dual of the coupling-constraint problem and reformulate it as a consensus…

Optimization and Control · Mathematics 2025-12-05 Chenyang Qiu , Yangyang Qian , Zongli Lin , Yacov A. Shamash

We suggest a conjugate subgradient type method without any line-search for minimization of convex non differentiable functions. Unlike the custom methods of this class, it does not require monotone decrease of the goal function and reduces…

Optimization and Control · Mathematics 2019-04-22 Igor Konnov

There are three key factors of a system of coupled oscillators that characterize the interaction among them: coupling (how to affect), delay (when to affect) and topology (whom to affect). For each of them, the existing work has mainly…

Optimization and Control · Mathematics 2015-06-15 Enrique Mallada , Ao Tang

We present a method for drawing isolines indicating regions of equal joint exceedance probability for bivariate data. The method relies on bivariate regular variation, a dependence framework widely used for extremes. This framework enables…

Methodology · Statistics 2017-10-17 Daniel Cooley , Emeric Thibaud , Federico Castillo , Michael F. Wehner

A cheapest stable nonconforming finite element method is presented for solving the incompressible flow in a square cavity without smoothing the corner singularities. The stable cheapest nonconforming finite element pair based on $P_1\times…

Numerical Analysis · Mathematics 2016-03-07 Roktaek Lim , Dongwoo Sheen

The results in this paper add useful tools to the theory of sets of desirable gambles, a growing toolbox for reasoning with partial probability assessments. We investigate how to combine a number of marginal coherent sets of desirable…

Artificial Intelligence · Computer Science 2014-02-05 Gert de Cooman , Enrique Miranda

Optimal dimensionality reduction methods are proposed for the Bayesian inference of a Gaussian linear model with additive noise in presence of overabundant data. Three different optimal projections of the observations are proposed based on…

Statistics Theory · Mathematics 2018-02-13 Loïc Giraldi , Olivier P. Le Maître , Ibrahim Hoteit , Omar M. Knio
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