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Graph-structured data is central to many scientific and industrial domains, where the goal is often to optimize objectives defined over graph structures. Given the combinatorial complexity of graph spaces, such optimization problems are…

Optimization and Control · Mathematics 2025-09-25 Shiqiang Zhang , Ruth Misener

This paper describes an extension to the constraint satisfaction problem (CSP) called MUSE CSP (MUltiply SEgmented Constraint Satisfaction Problem). This extension is especially useful for those problems which segment into multiple sets of…

Artificial Intelligence · Computer Science 2014-11-17 R. A Helzerman , M. P. Harper

A common representation of a three dimensional object in computer applications, such as graphics and design, is in the form of a triangular mesh. In many instances, individual or groups of triangles in such representation need to satisfy…

Optimization and Control · Mathematics 2019-04-08 Valentin R. Koch , Hung M. Phan

Despite encouraging recent progresses in ensemble approaches, classification methods seem to have reached a plateau in development. Further advances depend on a better understanding of geometrical and topological characteristics of point…

Computer Vision and Pattern Recognition · Computer Science 2007-05-23 Tin Kam Ho

Using derandomization, we provide an upper bound on the compression size of solutions to the graph coloring problem. In general, if solutions to a combinatorial problem exist with high probability and the probability is simple, then there…

Computational Complexity · Computer Science 2023-09-08 Samuel Epstein

We propose a new algorithm for finding an unknown number of geometric models, e.g., homographies. The problem is formalized as finding dominant model instances progressively without forming crisp point-to-model assignments. Dominant…

Computer Vision and Pattern Recognition · Computer Science 2023-04-18 Daniel Barath , Denys Rozumny , Ivan Eichhardt , Levente Hajder , Jiri Matas

Color coding is an algorithmic technique used in parameterized complexity theory to detect "small" structures inside graphs. The idea is to derandomize algorithms that first randomly color a graph and then search for an easily-detectable,…

Computational Complexity · Computer Science 2019-01-14 Max Bannach , Till Tantau

This article investigates the numerical approximation of shape optimization problems with PDE constraint on classes of convex domains. The convexity constraint provides a compactness property which implies well posedness of the problem.…

Optimization and Control · Mathematics 2018-10-26 Sören Bartels , Gerd Wachsmuth

Quantified constraints and Quantified Boolean Formulae are typically much more difficult to reason with than classical constraints, because quantifier alternation makes the usual notion of solution inappropriate. As a consequence, basic…

Logic in Computer Science · Computer Science 2007-05-25 Lucas Bordeaux , Marco Cadoli , Toni Mancini

In this paper, we consider the quadratic programming problems under finitely many convex quadratic constraints in Hilbert spaces. By using the Legendre property of quadratic forms or the compactness of operators in the presentations of…

Optimization and Control · Mathematics 2016-05-03 Vu Van Dong , Nguyen Nang Tam

The Distance Geometry Problem (DGP) seeks to find positions for a set of points in geometric space when some distances between pairs of these points are known. The so-called discretization assumptions allow to discretize the search space of…

Optimization and Control · Mathematics 2021-07-02 Moira MacNeil , Merve Bodur

Promise CSPs are a relaxation of constraint satisfaction problems where the goal is to find an assignment satisfying a relaxed version of the constraints. Several well-known problems can be cast as promise CSPs including approximate graph…

Computational Complexity · Computer Science 2018-07-16 Joshua Brakensiek , Venkatesan Guruswami

Random constraint satisfaction problems play an important role in computer science and combinatorics. For example, they provide challenging benchmark instances for algorithms and they have been harnessed in probabilistic constructions of…

Combinatorics · Mathematics 2020-05-27 Amin Coja-Oghlan , Tobias Kapetanopoulos , Noela Müller

Spectral properties of Coupled Map Lattices are described. Conditions for the stability of spatially homogeneous chaotic solutions are derived using linear stability analysis. Global stability analysis results are also presented. The…

Chaotic Dynamics · Physics 2009-11-07 J. Jost , M. P. Joy

Large-scale eigenvalue problems arise in various fields of science and engineering and demand computationally efficient solutions. In this study, we investigate the subspace approximation for parametric linear eigenvalue problems, aiming to…

LECTURE GIVEN AT TH2002. Given a set of Boolean variables, and some constraints between them, is it possible to find a configuration of the variables which satisfies all constraints? This problem, which is at the heart of combinatorial…

Disordered Systems and Neural Networks · Physics 2009-11-07 Marc Mezard

Localized patterns are coherent structures embedded in a quiescent state and occur in both discrete and continuous media across a wide range of applications. While it is well-understood how domain covering patterns (for example stripes and…

Pattern Formation and Solitons · Physics 2025-03-19 Jason J. Bramburger , Dan J. Hill , David J. B. Lloyd

This paper considers mathematical programs, whose constraints are expressed by a parameterized vector equilibrium problem. The latter is a well recognized framework, which is able to cover multicriteria optimization, vector variational…

Optimization and Control · Mathematics 2022-10-18 Amos Uderzo

This work deals with the presence of topological structures in models of two real scalar fields in the two-dimensional spacetime. The subject concerns the presence of a geometric constriction, which appears with a modification of the…

High Energy Physics - Theory · Physics 2024-03-11 D. Bazeia , M. A. Feitosa , R. Menezes , G. S. Santiago

We study computational and statistical consequences of problem geometry in stochastic and online optimization. By focusing on constraint set and gradient geometry, we characterize the problem families for which stochastic- and…

Optimization and Control · Mathematics 2025-07-17 Chen Cheng , Daniel Levy , John C. Duchi
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