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This paper presents a new type of genetic algorithm for the set covering problem. It differs from previous evolutionary approaches first because it is an indirect algorithm, i.e. the actual solutions are found by an external decoder…

Neural and Evolutionary Computing · Computer Science 2010-07-05 Uwe Aickelin

In this paper, we further investigate and refine the subspace-constrained preconditioning technique to enhance the theoretical and numerical convergence properties of randomized iterative methods for solving linear systems. In particular,…

Numerical Analysis · Mathematics 2026-05-29 Yonghan Sun , Hou-Duo Qi , Deren Han , Jiaxin Xie

In this paper we propose a variant of the linear least squares model allowing practitioners to partition the input features into groups of variables that they require to contribute similarly to the final result. The output allows…

Machine Learning · Computer Science 2024-07-17 Roberto Esposito , Mattia Cerrato , Marco Locatelli

Often computational models are too expensive to be solved in the entire domain of simulation, and a cheaper model would suffice away from the main zone of interest. We present for the concrete example of an evolution problem of advection…

Numerical Analysis · Mathematics 2014-09-15 Martin J. Gander , Laurence Halpern , Véronique Martin

We compare different analytical and numerical methods for studying the partitions of a finite system into fragments. We propose a new numerical method of exploring the partition space by generating the Markov chains of partitions based on…

Mathematical Physics · Physics 2009-10-31 A. S. Botvina , A. D. Jackson , I. N. Mishustin

Optimization problems with convex quadratic cost and polyhedral constraints are ubiquitous in signal processing, automatic control and decision-making. We consider here an enlarged problem class that allows to encode logical conditions and…

Optimization and Control · Mathematics 2026-04-09 Alberto De Marchi

In this paper, we develop a nonconvex approach to the problem of low-rank and sparse matrix decomposition. In our nonconvex method, we replace the rank function and the $l_{0}$-norm of a given matrix with a non-convex fraction function on…

Optimization and Control · Mathematics 2019-05-14 Angang Cui , Meng Wen , Haiyang Li , Jigen Peng

Matrix factorization is a popular approach for large-scale matrix completion. The optimization formulation based on matrix factorization can be solved very efficiently by standard algorithms in practice. However, due to the non-convexity…

Machine Learning · Computer Science 2016-11-18 Ruoyu Sun , Zhi-Quan Luo

We consider several basic questions pertaining to the geometry of image of a general quadratic map. In general the image of a quadratic map is non-convex, although there are several known classes of quadratic maps when the image is convex.…

Optimization and Control · Mathematics 2018-10-03 Anatoly Dymarsky , Elena Gryazina , Sergei Volodin , Boris Polyak

Over the last two decades, several fast, robust, and high-order accurate methods have been developed for solving the Poisson equation in complicated geometry using potential theory. In this approach, rather than discretizing the partial…

Numerical Analysis · Mathematics 2024-09-19 Fredrik Fryklund , Leslie Greengard , Shidong Jiang , Samuel Potter

We present a novel recursive algorithm for reducing a symmetric matrix to a triangular factorization which reveals the rank profile matrix. That is, the algorithm computes a factorization $\mathbf{P}^T\mathbf{A}\mathbf{P} =…

Numerical Analysis · Computer Science 2018-03-01 Jean-Guillaume Dumas , Clement Pernet

Cylindrical Algebraic Decomposition (CAD) by projection and lifting requires many iterated univariate resultants. It has been observed that these often factor, but to date this has not been used to optimise implementations of CAD. We…

Symbolic Computation · Computer Science 2023-08-21 James H. Davenport , Matthew England

Multi-attributed graph matching is a problem of finding correspondences between two sets of data while considering their complex properties described in multiple attributes. However, the information of multiple attributes is likely to be…

Computer Vision and Pattern Recognition · Computer Science 2017-04-25 Han-Mu Park , Kuk-Jin Yoon

Parallel and cyclic projection algorithms are proposed for minimizing the sum of a finite family of convex functions over the intersection of a finite family of closed convex subsets of a Hilbert space. These algorithms are of…

Optimization and Control · Mathematics 2019-01-08 Hong-Kun Xu , Vera Roshchina

The Hadamard decomposition is a powerful technique for data analysis and matrix compression, which decomposes a given matrix into the element-wise product of two or more low-rank matrices. In this paper, we develop an efficient algorithm to…

Machine Learning · Computer Science 2025-04-23 Samuel Wertz , Arnaud Vandaele , Nicolas Gillis

In this paper we develop a geometric approach to convex subdifferential calculus in finite dimensions with employing some ideas of modern variational analysis. This approach allows us to obtain natural and rather easy proofs of basic…

Optimization and Control · Mathematics 2015-10-06 Boris Mordukhovich , Nguyen Mau Nam

This article demonstrates how an understanding of the geometry of a family of cost functions can be used to develop efficient numerical algorithms for real-time optimisation. Crucially, it is not the geometry of the individual functions…

Optimization and Control · Mathematics 2012-12-11 Jonathan H. Manton

We investigate the possibilities to calculate vector partition functions by means of iterated partial fraction decomposition, as suggested by Beck (2004). Particularly, for an important type of families of rational functions, we describe an…

Combinatorics · Mathematics 2009-12-08 Thomas Bliem

Cut vertices, a generalization of matrix elements of local operators, are revisited, and an expansion in terms of minimally subtracted cut vertices is formulated. An extension of the formalism to deal with semi-inclusive deep inelastic…

High Energy Physics - Phenomenology · Physics 2009-10-30 M. Grazzini

Geometric programming problem is a powerful tool for solving some special type non-linear programming problems. It has a wide range of applications in optimization and engineering for solving some complex optimization problems. Many…

Data Structures and Algorithms · Computer Science 2010-03-25 A. K. Ojha , K. K. Biswal
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