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The Restricted Assignment Problem is a prominent special case of Scheduling on Parallel Unrelated Machines. For the strongest known linear programming relaxation, the configuration LP, we improve the non-constructive bound on its…

Data Structures and Algorithms · Computer Science 2019-08-21 Klaus Jansen , Lars Rohwedder

A longstanding problem related to floating-point implementation of numerical programs is to provide efficient yet precise analysis of output errors. We present a framework to compute lower bounds on largest absolute roundoff errors, for a…

Numerical Analysis · Computer Science 2018-02-13 Victor Magron

Recently, Czumaj et.al. (arXiv 2017) presented a parallel (almost) $2$-approximation algorithm for the maximum matching problem in only $O({(\log\log{n})^2})$ rounds of the massive parallel computation (MPC) framework, when the memory per…

Data Structures and Algorithms · Computer Science 2017-09-15 Sepehr Assadi

Linear programming has played a key role in the study of algorithms for combinatorial optimization problems. In the field of approximation algorithms, this is well illustrated by the uncapacitated facility location problem. A variety of…

Data Structures and Algorithms · Computer Science 2014-09-16 Hyung-Chan An , Mohit Singh , Ola Svensson

We investigate the computational complexity of min-max optimization under coupled constraints. The work of Daskalakis, Skoulakis, and Zampetakis [DSZ21] was the first to study min-max optimization through the lens of computational…

Computer Science and Game Theory · Computer Science 2026-05-28 Martino Bernasconi , Matteo Castiglioni , Andrea Celli , Gabriele Farina

In this paper, we present a new iterative rounding framework for many clustering problems. Using this, we obtain an $(\alpha_1 + \epsilon \leq 7.081 + \epsilon)$-approximation algorithm for $k$-median with outliers, greatly improving upon…

Data Structures and Algorithms · Computer Science 2018-04-09 Ravishankar Krishnaswamy , Shi Li , Sai Sandeep

A significant progress has been made in the past three decades over the study of combinatorial NP optimization problems and their associated optimization and approximate classes, such as NPO, PO, APX (or APXP), and PTAS. Unfortunately, a…

Computational Complexity · Computer Science 2016-01-07 Tomoyuki Yamakami

Makespan minimization on unrelated machines is a classic problem in approximation algorithms. No polynomial time $(2-\delta)$-approximation algorithm is known for the problem for constant $\delta> 0$. This is true even for certain special…

Data Structures and Algorithms · Computer Science 2014-10-29 Deeparnab Chakrabarty , Sanjeev Khanna , Shi Li

Finding the sparsest solutions to a tensor complementarity problem is generally NP-hard due to the nonconvexity and noncontinuity of the involved $\ell_0$ norm. In this paper, a special type of tensor complementarity problems with…

Spectral Theory · Mathematics 2015-05-06 Ziyan Luo , Liqun Qi , Naihua Xiu

Extended formulations are an important tool in polyhedral combinatorics. Many combinatorial optimization problems require an exponential number of inequalities when modeled as a linear program in the natural space of variables. However, by…

Optimization and Control · Mathematics 2024-06-07 Christoph Buchheim

The minimum linear ordering problem (MLOP) generalizes well-known combinatorial optimization problems such as minimum linear arrangement and minimum sum set cover. MLOP seeks to minimize an aggregated cost $f(\cdot)$ due to an ordering…

Data Structures and Algorithms · Computer Science 2023-10-30 Majid Farhadi , Swati Gupta , Shengding Sun , Prasad Tetali , Michael C. Wigal

We consider fairness in submodular maximization subject to a knapsack constraint, a fundamental problem with various applications in economics, machine learning, and data mining. In the model, we are given a set of ground elements, each…

Data Structures and Algorithms · Computer Science 2025-05-20 Lijun Li , Chenyang Xu , Liuyi Yang , Ruilong Zhang

A large number of problems in optimization, machine learning, signal processing can be effectively addressed by suitable semidefinite programming (SDP) relaxations. Unfortunately, generic SDP solvers hardly scale beyond instances with a few…

Optimization and Control · Mathematics 2016-03-15 Andrea Montanari

We address the classical knapsack problem and a variant in which an upper bound is imposed on the number of items that can be selected. We show that appropriate combinations of rounding techniques yield novel and powerful ways of rounding.…

Computational Complexity · Computer Science 2007-05-23 Monaldo Mastrolilli , Marcus Hutter

We consider the {\em matroid median} problem \cite{KrishnaswamyKNSS11}, wherein we are given a set of facilities with opening costs and a matroid on the facility-set, and clients with demands and connection costs, and we seek to open an…

Data Structures and Algorithms · Computer Science 2016-09-30 Chaitanya Swamy

It is known that there is no EPTAS for the $m$-dimensional knapsack problem unless $W[1] = FPT$. It is true already for the case, when $m = 2$. But, an FPTAS still can exist for some other particular cases of the problem. In this note, we…

Computational Complexity · Computer Science 2022-11-30 D. V. Gribanov

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

We consider various {\em multi-vehicle versions of the minimum latency problem}. There is a fleet of $k$ vehicles located at one or more depot nodes, and we seek a collection of routes for these vehicles that visit all nodes so as to…

Data Structures and Algorithms · Computer Science 2014-11-18 Ian Post , Chaitanya Swamy

We give a lower bound on the iteration complexity of a natural class of Lagrangean-relaxation algorithms for approximately solving packing/covering linear programs. We show that, given an input with $m$ random 0/1-constraints on $n$…

Data Structures and Algorithms · Computer Science 2015-11-23 Phil Klein , Neal E. Young

We present combinatorial and parallelizable algorithms for maximization of a submodular function, not necessarily monotone, with respect to a size constraint. We improve the best approximation factor achieved by an algorithm that has…

Data Structures and Algorithms · Computer Science 2024-02-21 Yixin Chen , Alan Kuhnle