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We introduce and discuss (local) symmetries of geometric structures. These symmetries generalize the classical (locally) symmetric spaces to various other geometries. Our main tools are homogeneous Cartan geometries and their explicit…

Differential Geometry · Mathematics 2012-07-03 Jan Gregorovič

We propose a framework for unified analysis of mixed methods for elasticity with weakly symmetric stress. Based on a commuting diagram in the weakly symmetric elasticity complex and extending a previous stability result, stable mixed…

Numerical Analysis · Mathematics 2015-10-12 Jeonghun J. Lee

This paper presents an efficient algorithm for the approximation of the rank-one convex hull in the context of nonlinear solid mechanics. It is based on hierarchical rank-one sequences and simultaneously provides first and second derivative…

Computational Engineering, Finance, and Science · Computer Science 2024-05-28 Maximilian Köhler , Timo Neumeier , Malte. A. Peter , Daniel Peterseim , Daniel Balzani

In our previous paper, we presented the combinatorial theory for minimal isostatic pinned frameworks - Assur graphs - which arise in the analysis of mechanical linkages. In this paper we further explore the geometric properties of Assur…

Metric Geometry · Mathematics 2016-09-08 Brigitte Servatius , Offer Shai , Walter Whiteley

The classical continuous mixed formulation of linear elasticity with pointwise symmetric stresses allows for a conforming finite element discretization with piecewise polynomials of degree at least three. Symmetric stress approximations of…

Numerical Analysis · Mathematics 2025-03-17 Carsten Carstensen , Norbert Heuer

A graph $\Gamma$ is $G$-symmetric if $G$ is a group of automorphisms of $\Gamma$ which is transitive on the set of ordered pairs of adjacent vertices of $\Gamma$. If $V(\Gamma)$ admits a nontrivial $G$-invariant partition ${\cal B}$ such…

Combinatorics · Mathematics 2019-08-06 Yu Qing Chen , Teng Fang , Sanming Zhou

We explore the role of group symmetries in binary classification tasks, presenting a novel framework that leverages the principles of Neyman-Pearson optimality. Contrary to the common intuition that larger symmetry groups lead to improved…

Machine Learning · Computer Science 2024-08-19 Vishal S. Ngairangbam , Michael Spannowsky

A rigidity theory is developed for frameworks in a metric space with two types of distance constraints. Mixed sparsity graph characterisations are obtained for the infinitesimal and continuous rigidity of completely regular bar-joint…

Metric Geometry · Mathematics 2019-08-26 Anthony Nixon , Stephen Power

Estimation of Markov Random Field and covariance models from high-dimensional data represents a canonical problem that has received a lot of attention in the literature. A key assumption, widely employed, is that of {\em sparsity} of the…

Optimization and Control · Mathematics 2018-05-16 Davoud Ataee Tarzanagh , George Michailidis

This paper characterizes hierarchical clustering methods that abide by two previously introduced axioms -- thus, denominated admissible methods -- and proposes tractable algorithms for their implementation. We leverage the fact that, for…

Machine Learning · Computer Science 2016-07-22 Gunnar Carlsson , Facundo Mémoli , Alejandro Ribeiro , Santiago Segarra

Variable selection for models including interactions between explanatory variables often needs to obey certain hierarchical constraints. The weak or strong structural hierarchy requires that the existence of an interaction term implies at…

Statistics Theory · Mathematics 2016-11-10 Yiyuan She , Zhifeng Wang , He Jiang

In this paper we present a unified framework for solving a general class of problems arising in the context of set-membership estimation/identification theory. More precisely, the paper aims at providing an original approach for the…

Systems and Control · Computer Science 2016-11-18 Vito Cerone , Jean-Bernard Lasserre , Dario Piga , Diego Regruto

Roadmaps constructed by many sampling-based motion planners coincide, in the absence of obstacles, with standard models of random geometric graphs (RGGs). Those models have been studied for several decades and by now a rich body of…

Robotics · Computer Science 2016-02-18 Kiril Solovey , Oren Salzman , Dan Halperin

Equivariant neural networks have proven to be effective for tasks with known underlying symmetries. However, optimizing equivariant networks can be tricky and best training practices are less established than for standard networks. In…

Machine Learning · Computer Science 2025-11-04 YuQing Xie , Tess Smidt

Ensemble learning is traditionally justified as a variance-reduction strategy, explaining its strong performance for unstable predictors such as decision trees. This explanation, however, does not account for ensembles constructed from…

Machine Learning · Statistics 2025-12-30 Ernest Fokoué

Using the theory of group action, we first introduce the concept of the automorphism group of an exponential family or a graphical model, thus formalizing the general notion of symmetry of a probabilistic model. This automorphism group…

Artificial Intelligence · Computer Science 2013-09-27 Hung Bui , Tuyen Huynh , Sebastian Riedel

We introduce group crosscoders, an extension of crosscoders that systematically discover and analyse symmetrical features in neural networks. While neural networks often develop equivariant representations without explicit architectural…

Machine Learning · Computer Science 2024-11-04 Liv Gorton

An important problem in geometric reasoning is to find the configuration of a collection of geometric bodies so as to satisfy a set of given constraints. Recently, it has been suggested that this problem can be solved efficiently by…

Artificial Intelligence · Computer Science 2009-09-25 S. Bhansali , G. A. Kramer , T. J. Hoar

Orthogonal group synchronization is the problem of estimating $n$ elements $Z_1, \ldots, Z_n$ from the $r \times r$ orthogonal group given some relative measurements $R_{ij} \approx Z_i^{}Z_j^{-1}$. The least-squares formulation is…

Optimization and Control · Mathematics 2024-04-22 Andrew D. McRae , Nicolas Boumal

The design of porous infill structures presents significant challenges due to their complex geometric configurations, such as the accurate representation of geometric boundaries and the control of localized maximum stress. In current…

Optimization and Control · Mathematics 2025-10-14 Shuzhi Xu , Hiroki Kawabe , Kentaro Yaji