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A semi-projective representation is a homomorphism of a finite group into the group of semi-projective transformations of a finite dimensional vector space over a field. Schur's concept of a representation group for projective…

Group Theory · Mathematics 2023-05-05 Massimiliano Alessandro , Christian Gleissner , Julia Kotonski

We show that the set of realizations of a given dimension of a max-plus linear sequence is a finite union of polyhedral sets, which can be computed from any realization of the sequence. This yields an (expensive) algorithm to solve the…

Data Structures and Algorithms · Computer Science 2011-03-14 Vincent Blondel , Stéphane Gaubert , Natacha Portier

Knowing the symmetries of a polyhedron can be very useful for the analysis of its structure as well as for practical polyhedral computations. In this note, we study symmetry groups preserving the linear, projective and combinatorial…

Hermitian linear matrix pencils are ubiquitous in control theory, operator systems, semidefinite optimization, and real algebraic geometry. This survey reviews the fundamental features of the matricial solution set of a linear matrix…

Functional Analysis · Mathematics 2024-07-12 Jurij Volčič

Given any finite set of nonnegative integers, there exists a closed convex set whose facial dimension signature coincides with this set of integers, that is, the dimensions of its nonempty faces comprise exactly this set of integers. In…

Optimization and Control · Mathematics 2024-08-26 Vera Roshchina , Levent Tunçel

Using semi-tensor product of matrices, the structures of several kinds of symmetric games are investigated via the linear representation of symmetric group in the structure vector of games as its representation space. First of all, the…

Computer Science and Game Theory · Computer Science 2017-03-09 Daizhan Cheng , Ting Liu

This paper deals with faces and facets of the family-variable polytope and the characteristic-imset polytope, which are special polytopes used in integer linear programming approaches to statistically learn Bayesian network structure. A…

Combinatorics · Mathematics 2022-03-29 James Cussens , David Haws , Milan Studeny

In this paper we construct a hierarchy of multivariate polynomial approximation kernels via semidefinite programming. We give details on the implementation of the semidefinite programs defining the kernels. Finally, we show how a symmetry…

Optimization and Control · Mathematics 2023-07-19 Felix Kirschner , Etienne de Klerk

We consider the question of which nonconvex sets can be represented exactly as the feasible sets of mixed-integer convex optimization problems. We state the first complete characterization for the case when the number of possible integer…

Optimization and Control · Mathematics 2017-06-20 Miles Lubin , Ilias Zadik , Juan Pablo Vielma

We present algorithmic, complexity, and implementation results on the problem of sampling points from a spectrahedron, that is the feasible region of a semidefinite program. Our main tool is geometric random walks. We analyze the arithmetic…

Computational Geometry · Computer Science 2020-10-09 Apostolos Chalkis , Ioannis Emiris , Vissarion Fisikopoulos , Panagiotis Repouskos , Elias Tsigaridas

Quasi-separable matrices are a class of rank-structured matriceswidely used in numerical linear algebra and of growing interestin computer algebra, with applications in e.g. the linearization ofpolynomial matrices. Various representation…

Symbolic Computation · Computer Science 2023-02-10 Clément Pernet , Hippolyte Signargout , Gilles Villard

We show that the closed convex hull of any one-dimensional semi-algebraic subset of R^n has a semidefinite representation, meaning that it can be written as a linear projection of the solution set of some linear matrix inequality. This is…

Algebraic Geometry · Mathematics 2017-09-19 Claus Scheiderer

We present a general framework of semi-supervised dimensionality reduction for manifold learning which naturally generalizes existing supervised and unsupervised learning frameworks which apply the spectral decomposition. Algorithms derived…

Machine Learning · Computer Science 2009-07-29 Ratthachat Chatpatanasiri , Boonserm Kijsirikul

Semidefinite programming (SDP) is a fundamental class of convex optimization problems with diverse applications in mathematics, engineering, machine learning, and related disciplines. This paper investigates the application of the…

Optimization and Control · Mathematics 2025-10-15 Zilong Cui , Ran Gu

We extend \cite{chen2025srkbp} by analyzing the complexity of the $k$-block-positivity testing algorithm that stems from the optimization problem in Definition \ref{definition:SDP-k-block-positivity}. In this paper, we investigate a…

Quantum Physics · Physics 2026-03-17 Qian Chen , Benoît Collins

Regularization techniques are widely employed in optimization-based approaches for solving ill-posed inverse problems in data analysis and scientific computing. These methods are based on augmenting the objective with a penalty function,…

Optimization and Control · Mathematics 2021-06-08 Yong Sheng Soh , Venkat Chandrasekaran

We survey recent generalizations and improvements of the linear programming method that involve semidefinite programming. A general framework using group representations and tools from graph theory is provided.

Information Theory · Computer Science 2010-09-09 Christine Bachoc

Let $\mathrm{R}$ be a real closed field. We prove that for any fixed $d$, the equivariant rational cohomology groups of closed symmetric semi-algebraic subsets of $\mathrm{R}^k$ defined by polynomials of degrees bounded by $d$ vanishes in…

Algebraic Topology · Mathematics 2018-02-15 Saugata Basu , Cordian Riener

We consider the problem of estimating the locations of a set of points in a k-dimensional euclidean space given a subset of the pairwise distance measurements between the points. We focus on the case when some fraction of these measurements…

Information Theory · Computer Science 2012-10-19 Venkatesan Ekambaram , Giulia Fanti , Kannan Ramchandran

Circuits play a fundamental role in polyhedral theory and linear programming. For instance, circuits are used as step directions in various augmentation schemes for solving linear programs or to leave degenerate vertices while running the…

Optimization and Control · Mathematics 2019-07-01 Steffen Borgwardt , Charles Viss