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Related papers: Computational Approaches to Lattice Packing and Co…

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Let $X$ be a finite set in $Z^d$. We consider the problem of optimizing linear function $f(x) = c^T x$ on $X$, where $c\in Z^d$ is an input vector. We call it a problem $X$. A problem $X$ is related with linear program $\max\limits_{x \in…

Computational Complexity · Computer Science 2018-04-18 Aleksandr Maksimenko

This paper presents rigorous forward error bounds for linear conic optimization problems. The error bounds are formulated in a quite general framework; the underlying vector spaces are not required to be finite-dimensional, and the convex…

Optimization and Control · Mathematics 2007-07-31 Christian Jansson

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

The Two-dimensional Bin Packing Problem calls for packing a set of rectangular items into a minimal set of larger rectangular bins. Items must be packed with their edges parallel to the borders of the bins, cannot be rotated and cannot…

Optimization and Control · Mathematics 2019-09-17 Jean-François Côté , Mohamed Haouari , Manuel Iori

L1 -penalized regression methods such as the Lasso (Tibshirani 1996) that achieve both variable selection and shrinkage have been very popular. An extension of this method is the Fused Lasso (Tibshirani and Wang 2007), which allows for the…

Computation · Statistics 2010-12-01 Holger Höfling , Harald Binder , Martin Schumacher

Given a set of $n$ points in the plane, the Unit Disk Cover (UDC) problem asks to compute the minimum number of unit disks required to cover the points, along with a placement of the disks. The problem is NP-hard and several approximation…

Computational Geometry · Computer Science 2022-05-05 Rachel Friederich , Matthew Graham , Anirban Ghosh , Brian Hicks , Ronald Shevchenko

We present a massively parallel algorithm, with near-linear memory per machine, that computes a $(2+\varepsilon)$-approximation of minimum-weight vertex cover in $O(\log\log d)$ rounds, where $d$ is the average degree of the input graph.…

Data Structures and Algorithms · Computer Science 2020-05-22 Mohsen Ghaffari , Ce Jin , Daan Nilis

Packing and covering linear programs (PC-LPs) form an important class of linear programs (LPs) across computer science, operations research, and optimization. In 1993, Luby and Nisan constructed an iterative algorithm for approximately…

Data Structures and Algorithms · Computer Science 2018-02-28 Zeyuan Allen-Zhu , Lorenzo Orecchia

A new algorithm for solving large-scale convex optimization problems with a separable objective function is proposed. The basic idea is to combine three techniques: Lagrangian dual decomposition, excessive gap and smoothing. The main…

Optimization and Control · Mathematics 2011-12-01 Tran Dinh Quoc , Carlo Savorgnan , Moritz Diehl

We give a deterministic O(log n)^n algorithm for the {\em Shortest Vector Problem (SVP)} of a lattice under {\em any} norm, improving on the previous best deterministic bound of n^O(n) for general norms and nearly matching the bound of…

Computational Complexity · Computer Science 2011-07-28 Daniel Dadush , Santosh Vempala

In this paper we propose a new inexact dual decomposition algorithm for solving separable convex optimization problems. This algorithm is a combination of three techniques: dual Lagrangian decomposition, smoothing and excessive gap. The…

Optimization and Control · Mathematics 2013-02-11 Quoc Tran Dinh , Ion Necoara , Moritz Diehl

Coverage problems are central in optimization and have a wide range of applications in data mining and machine learning. While several distributed algorithms have been developed for coverage problems, the existing methods suffer from…

Data Structures and Algorithms · Computer Science 2017-03-13 MohammadHossein Bateni , Hossein Esfandiari , Vahab Mirrokni

This work studies the combinatorial optimization problem of finding an optimal core tensor shape, also called multilinear rank, for a size-constrained Tucker decomposition. We give an algorithm with provable approximation guarantees for its…

Data Structures and Algorithms · Computer Science 2024-06-19 Mehrdad Ghadiri , Matthew Fahrbach , Gang Fu , Vahab Mirrokni

We prove upper bounds on the order of convergence of lattice based algorithms for numerical integration in function spaces of dominating mixed smoothness on the unit cube with homogeneous boundary condition. More precisely, we study…

Numerical Analysis · Mathematics 2019-08-15 Josef Dick , Friedrich Pillichshammer , Kosuke Suzuki , Mario Ullrich , Takehito Yoshiki

We propose a randomized lattice algorithm for approximating multivariate periodic functions over the $d$-dimensional unit cube from the weighted Korobov space with mixed smoothness $\alpha > 1/2$ and product weights…

Numerical Analysis · Mathematics 2025-08-26 Mou Cai , Takashi Goda , Yoshihito Kazashi

We study the problem of enumerating Tarski fixed points on finite lattices. We derive query complexity lower bounds for finding three or more Tarski fixed points of isotone maps and the subclasses of increasing and decreasing isotone maps.…

Discrete Mathematics · Computer Science 2026-04-28 Julian Müller

Meshes composed of well-centered simplices have nice orthogonal dual meshes (the dual Voronoi diagram). This is useful for certain numerical algorithms that prefer such primal-dual mesh pairs. We prove that well-centered meshes also have…

Computational Geometry · Computer Science 2010-01-25 Evan VanderZee , Anil N. Hirani , Damrong Guoy , Edgar Ramos

In two-dimensional geometric knapsack problem, we are given a set of n axis-aligned rectangular items and an axis-aligned square-shaped knapsack. Each item has integral width, integral height and an associated integral profit. The goal is…

Data Structures and Algorithms · Computer Science 2021-03-18 Arindam Khan , Arnab Maiti , Amatya Sharma , Andreas Wiese

We construct integer error-correcting codes and covering codes for the limited-magnitude error channel with more than one error. The codes are lattices that pack or cover the space with the appropriate error ball. Some of the constructions…

Information Theory · Computer Science 2020-06-01 Hengjia Wei , Xin Wang , Moshe Schwartz

Computer simulations serve as powerful tools for scientists and engineers to gain insights into complex systems. Less costly than physical experiments, computer experiments sometimes involve large number of trials. Conventional design…

Methodology · Statistics 2025-06-06 Xu He , Junpeng Gong , Zhaohui Li
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