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A new error bound for the linear complementarity problem when the matrix involved is a B-matrix is presented, which improves the corresponding result in [C.Q. Li et al., A new error bound for linear complementarity problems for B-matrices.…

Numerical Analysis · Mathematics 2016-10-21 Lei Gao , Chaoqian Li

New error bounds for the linear complementarity problems are given respectively when the involved matrices are Nekrasov matrices and B-Nekrasov matrices. Numerical examples are given to show that new bounds are better respectively than…

Numerical Analysis · Mathematics 2016-07-20 Chaoqian Li , Pingfan Dai , Yaotang Li

In this article we establish error bound for linear complementarity problem with $P$-matrix using plus function. We introduce a fundamental quantity associated with a $P$-matrix and show how this quantity is useful in deriving error bounds…

Optimization and Control · Mathematics 2022-09-02 Bharat Kumar , Deepmala , A. Dutta , A. K. Das

Error bounds have been studied for more than seventy years, beginning with the seminal result of Hoffman (1952) [{\it J. Res. Natl. Bur. Standards}, 49 (1952), 263--265], which establishes an upper bound for the distance from an arbitrary…

Optimization and Control · Mathematics 2026-05-25 Zhou Wei , Michel Thera , Jen-Chih Yao

Absolute value equations, due to their relation to the linear complementarity problem, have been intensively studied recently. In this paper, we present error bounds for absolute value equations. Along with the error bounds, we introduce an…

Optimization and Control · Mathematics 2020-01-20 Moslem Zamani , Milan Hladic

We propose an algorithm for solving bound-constrained mathematical programs with complementarity constraints on the variables. Each iteration of the algorithm involves solving a linear program with complementarity constraints in order to…

Optimization and Control · Mathematics 2022-01-14 Christian Kirches , Jeffrey Larson , Sven Leyffer , Paul Manns

In this note, we prove that the problem of computing the linear discrepancy of a given matrix is $\Pi_2$-hard, even to approximate within $9/8 - \epsilon$ factor for any $\epsilon > 0$. This strengthens the NP-hardness result of Li and…

Computational Complexity · Computer Science 2021-07-06 Pasin Manurangsi

In this article, we establish a class of new accelerated modulus-based iteration methods for solving the linear complementarity problem. When the system matrix is an $H_+$-matrix, we present appropriate criteria for the convergence…

Optimization and Control · Mathematics 2023-05-05 Bharat Kumar , Deepmala , A. K. Das

We derive a linear programming bound on the maximum cardinality of error-correcting codes in the sum-rank metric. Based on computational experiments on relatively small instances, we observe that the obtained bounds outperform all…

Combinatorics · Mathematics 2024-06-25 Aida Abiad , Alexander L. Gavrilyuk , Antonina P. Khramova , Ilia Ponomarenko

Many problems in computer science and applied mathematics require rounding a vector $\mathbf{w}$ of fractional values lying in the interval $[0,1]$ to a binary vector $\mathbf{x}$ so that, for a given matrix $\mathbf{A}$,…

Data Structures and Algorithms · Computer Science 2020-08-04 Lily Li , Aleksandar Nikolov

In certain applications involving the solution of a Bayesian inverse problem, it may not be possible or desirable to evaluate the full posterior, e.g. due to the high computational cost of doing so. This problem motivates the use of…

Statistics Theory · Mathematics 2024-02-27 Han Cheng Lie , T. J. Sullivan , Aretha Teckentrup

We consider adjustable robust linear complementarity problems and extend the results of Biefel et al. (2022) towards convex and compact uncertainty sets. Moreover, for the case of polyhedral uncertainty sets, we prove that computing an…

Optimization and Control · Mathematics 2023-11-02 Christian Biefel , Martin Schmidt

Let $H$ be a real Hilbert space. In this short note, using some of the properties of bounded linear operators with closed range defined on $H$, certain bounds for a specific convex subset of the solution set of infinite linear…

Functional Analysis · Mathematics 2020-06-30 Projesh Nath Choudhury , M. Rajesh Kannan , K. C. Sivakumar

In this paper, we develop a relative error bound for nuclear norm regularized matrix completion, with the focus on the completion of full-rank matrices. Under the assumption that the top eigenspaces of the target matrix are incoherent, we…

Machine Learning · Computer Science 2024-05-30 Lijun Zhang , Tianbao Yang , Rong Jin , Zhi-Hua Zhou

Linear differential equations and recurrences reveal many properties about their solutions. Therefore, these equations are well-suited for representing solutions and computing with special functions. We identify a large class of existing…

Symbolic Computation · Computer Science 2026-01-14 Louis Gaillard

In this paper we present a new bound obtained with the probabilistic method for the solution of the Set Covering problem with unit costs. The bound is valid for problems of fixed dimension, thus extending previous similar asymptotic…

Combinatorics · Mathematics 2014-07-18 Giovanni Felici , Sokol Ndreca , Aldo Procacci , Benedetto Scoppola

We consider the linear complementarity problem with uncertain data modeled by intervals, representing the range of possible values. Many properties of the linear complementarity problem (such as solvability, uniqueness, convexity, finite…

Optimization and Control · Mathematics 2025-10-07 Milan Hladík

In the first part of this study, a convex-constrained penalized formulation was studied for a class of constant modulus (CM) problems. In particular, the error bound techniques were shown to play a vital role in providing exact penalization…

Signal Processing · Electrical Eng. & Systems 2024-11-12 Junbin Liu , Ya Liu , Wing-Kin Ma , Mingjie Shao , Anthony Man-Cho So

We prove lower bounds of order $n\log n$ for both the problem to multiply polynomials of degree $n$, and to divide polynomials with remainder, in the model of bounded coefficient arithmetic circuits over the complex numbers. These lower…

Computational Complexity · Computer Science 2007-05-23 Peter Buergisser , Martin Lotz

Due to their importance in both data analysis and numerical algorithms, low rank approximations have recently been widely studied. They enable the handling of very large matrices. Tight error bounds for the computationally efficient…

Numerical Analysis · Mathematics 2023-04-06 Frank de Hoog , Markus Hegland
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