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We introduce a generalized framework for studying higher-order versions of the multiscale method known as Localized Orthogonal Decomposition. Through a suitable reformulation, we are able to accommodate both conforming and nonconforming…

Numerical Analysis · Mathematics 2025-06-25 Moritz Hauck , Alexei Lozinski , Roland Maier

Datalog reasoning based on the semina\"ive evaluation strategy evaluates rules using traditional join plans, which often leads to redundancy and inefficiency in practice, especially when the rules are complex. Hypertree decompositions help…

Databases · Computer Science 2023-05-16 Xinyue Zhang , Pan Hu , Yavor Nenov , Ian Horrocks

This paper provides a theoretical and numerical investigation of a penalty decomposition scheme for the solution of optimization problems with geometric constraints. In particular, we consider some situations where parts of the constraints…

Optimization and Control · Mathematics 2023-03-23 Matteo Lapucci , Christian Kanzow

Detectability of failures of linear programming (LP) decoding and the potential for improvement by adding new constraints motivate the use of an adaptive approach in selecting the constraints for the underlying LP problem. In this paper, we…

Information Theory · Computer Science 2007-07-13 Mohammad H. Taghavi , Paul H. Siegel

Chordal and factor-width decomposition methods for semidefinite programming and polynomial optimization have recently enabled the analysis and control of large-scale linear systems and medium-scale nonlinear systems. Chordal decomposition…

Optimization and Control · Mathematics 2021-11-23 Yang Zheng , Giovanni Fantuzzi , Antonis Papachristodoulou

The sparse generalized eigenvalue problem arises in a number of standard and modern statistical learning models, including sparse principal component analysis, sparse Fisher discriminant analysis, and sparse canonical correlation analysis.…

Numerical Analysis · Computer Science 2019-03-05 Ganzhao Yuan , Li Shen , Wei-Shi Zheng

Detectability of failures of linear programming (LP) decoding and its potential for improvement by adding new constraints motivate the use of an adaptive approach in selecting the constraints for the LP problem. In this paper, we make a…

Information Theory · Computer Science 2007-07-13 Mohammad H. Taghavi N. , Paul H. Siegel

Literature on Constraint Satisfaction exhibits the definition of several structural properties that can be possessed by CSPs, like (in)consistency, substitutability or interchangeability. Current tools for constraint solving typically…

Artificial Intelligence · Computer Science 2014-01-16 Lucas Bordeaux , Marco Cadoli , Toni Mancini

The notion of $\mathcal{H}$-treewidth, where $\mathcal{H}$ is a hereditary graph class, was recently introduced as a generalization of the treewidth of an undirected graph. Roughly speaking, a graph of $\mathcal{H}$-treewidth at most $k$…

Data Structures and Algorithms · Computer Science 2023-06-30 Bart M. P. Jansen , Jari J. H. de Kroon , Michal Wlodarczyk

Combinatorial problems stated as Constraint Satisfaction Problems (CSP) are examined. It is shown by example that any algorithm designed for the original CSP, and involving the AllDifferent constraint, has at least the same level of…

Artificial Intelligence · Computer Science 2020-12-15 Geoff Harris

In this article, we show that the algorithm of maintaining expander decompositions in graphs undergoing edge deletions directly by removing sparse cuts repeatedly can be made efficient. Formally, for an $m$-edge undirected graph $G$, we say…

Data Structures and Algorithms · Computer Science 2023-01-24 Yiding Hua , Rasmus Kyng , Maximilian Probst Gutenberg , Zihang Wu

The Constraint Satisfaction Problem (CSP) is a problem of computing a homomorphism $\mathbf{R}\to \mathbf{\Gamma}$ between two relational structures, where $\mathbf{R}$ is defined over a domain $V$ and $\mathbf{\Gamma}$ is defined over a…

Computational Complexity · Computer Science 2023-11-21 Rustem Takhanov

A key step in reverse engineering neural networks is to decompose them into simpler parts that can be studied in relative isolation. Linear parameter decomposition -- a framework that has been proposed to resolve several issues with current…

Machine Learning · Computer Science 2025-09-05 Lucius Bushnaq , Dan Braun , Lee Sharkey

This paper investigates the reconfiguration variant of the Constraint Satisfaction Problem (CSP), referred to as the Reconfiguration CSP (RCSP). Given a CSP instance and two of its solutions, RCSP asks whether one solution can be…

Data Structures and Algorithms · Computer Science 2026-03-06 Kei Kimura

We propose new algorithms for computing triangular decompositions of polynomial systems incrementally. With respect to previous works, our improvements are based on a {\em weakened} notion of a polynomial GCD modulo a regular chain, which…

Symbolic Computation · Computer Science 2011-04-06 Changbo Chen , Marc Moreno Maza

The Constraint Satisfaction Problem (CSP) has been intensively studied in many areas of computer science and mathematics. The approach to the CSP based on tools from universal algebra turned out to be the most successful one to study the…

Logic · Mathematics 2025-01-16 Andrei A. Bulatov

In this paper, we propose an incremental algorithm for computing cylindrical algebraic decompositions. The algorithm consists of two parts: computing a complex cylindrical tree and refining this complex tree into a cylindrical tree in real…

Symbolic Computation · Computer Science 2012-10-23 Changbo Chen , Marc Moreno Maza

The CLP scheme uses Horn clauses and SLD resolution to generate multiple constraint satisfaction problems (CSPs). The possible CSPs include rational trees (giving Prolog) and numerical algorithms for solving linear equations and linear…

Programming Languages · Computer Science 2010-02-09 M. H. van Emden

Supertree construction is the process by which a set of phylogenetic trees, each on a subset of the overall set X of species, is combined into a tree on the full set S. The traditional use of supertree methods is the assembly of a large…

Populations and Evolution · Quantitative Biology 2018-05-10 Tandy Warnow

Expander decompositions of graphs have significantly advanced the understanding of many classical graph problems and led to numerous fundamental theoretical results. However, their adoption in practice has been hindered due to their…

Data Structures and Algorithms · Computer Science 2026-04-27 Kathrin Hanauer , Monika Henzinger , Robin Münk , Harald Räcke , Maximilian Vötsch