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We present a polynomial time algorithm to approximately scale tensors of any format to arbitrary prescribed marginals (whenever possible). This unifies and generalizes a sequence of past works on matrix, operator and tensor scaling. Our…

Data Structures and Algorithms · Computer Science 2020-03-10 Peter Bürgisser , Cole Franks , Ankit Garg , Rafael Oliveira , Michael Walter , Avi Wigderson

Partitioning a sequence of length $n$ into $k$ coherent segments (Seg) is one of the classic optimization problems. As long as the optimization criterion is additive, Seg can be solved exactly in $O(n^2k)$ time using a classic dynamic…

Data Structures and Algorithms · Computer Science 2019-02-06 Nikolaj Tatti

In this paper we consider several constrained activity scheduling problems in the time and space domains, like finding activity orderings which optimize the values of several objective functions (time scheduling) or finding optimal…

Data Structures and Algorithms · Computer Science 2009-06-09 Madalina Ecaterina Andreica , Mugurel Ionut Andreica , Angela Andreica

Gradient-based algorithms, popular strategies to optimization problems, are essential for many modern machine-learning techniques. Theoretically, extreme points of certain cost functions can be found iteratively along the directions of the…

Quantum Physics · Physics 2021-04-07 Keren Li , Pan Gao , Shijie Wei , Jiancun Gao , Guilu Long

In recent years, several powerful techniques have been developed to design {\em randomized} polynomial-space parameterized algorithms. In this paper, we introduce an enhancement of color coding to design deterministic polynomial-space…

Data Structures and Algorithms · Computer Science 2017-12-20 Gregory Gutin , Felix Reidl , Magnus Wahlström , Meirav Zehavi

Given a simple polygon $ \mathcal {P} $ of $ n $ vertices in the Plane. We study the problem of computing the visibility area from a given viewpoint $ q $ inside $ \mathcal {P} $ where only sub-linear variables are allowed for working…

Computational Geometry · Computer Science 2018-04-06 Hamid Hoorfar , Alireza Bagheri

Polynomial optimization problems over binary variables can be expressed as integer programs using a linearization with extra monomials in addition to those arising in the given polynomial. We characterize when such a linearization yields an…

Discrete Mathematics · Computer Science 2020-05-18 Christopher Hojny , Marc E. Pfetsch , Matthias Walter

We study an interval ordering problem introduced by D\"urr et al. [Discrete Appl. Math. 2012] which is motivated by applications in bioinformatics. The task is to order a given set of n intervals with the goal of minimizing a certain…

Data Structures and Algorithms · Computer Science 2026-05-08 Simeon Pawlowski , Vincent Froese

The Clique Problem has a reduction to the Maximum Flow Network Interdiction Problem. We review the reduction to evolve a polynomial time algorithm for the Clique Problem. A computer program in C language has been written to validate the…

Data Structures and Algorithms · Computer Science 2020-01-01 Pawan Tamta , B. P. Pande , H. S. Dhami

Research efforts of the past fifty years have led to a development of linear integer programming as a mature discipline of mathematical optimization. Such a level of maturity has not been reached when one considers nonlinear systems subject…

Optimization and Control · Mathematics 2017-01-03 Raymond Hemmecke , Matthias Köppe , Jon Lee , Robert Weismantel

In this paper, we give an algorithm that finds an epsilon-approximate solution to a mixed integer quadratic programming (MIQP) problem. The algorithm runs in polynomial time if the rank of the quadratic function and the number of integer…

Optimization and Control · Mathematics 2022-11-30 Alberto Del Pia

We present a polynomial time dynamic programming algorithm for optimal partitions in the shortest path metric induced by a tree. This resolves, among other things, the exact complexity status of the optimal partition problems in one…

Data Structures and Algorithms · Computer Science 2012-12-17 Marek Karpinski , Andrzej Lingas , Dzmitry Sledneu

Low-rank approximations of data matrices are an important dimensionality reduction tool in machine learning and regression analysis. We consider the case of categorical variables, where it can be formulated as the problem of finding…

Machine Learning · Computer Science 2018-03-14 Reka Kovacs , Oktay Gunluk , Raphael Hauser

Building on the blueprint from Goemans and Williamson (1995) for the Max-Cut problem, we construct a polynomial-time approximation algorithm for orthogonally constrained quadratic optimization problems. First, we derive a semidefinite…

Optimization and Control · Mathematics 2026-03-17 Ryan Cory-Wright , Jean Pauphilet

Linear Programming (LP) is widely applied in industry and is a key component of various other mathematical problem-solving techniques. Recent work introduced an LP compiler translating polynomial-time, polynomial-space algorithms into…

Programming Languages · Computer Science 2025-09-17 Shermin Khosravi , David Bremner

This paper addresses the problem of managing rotational load shedding schedules for a power distribution network with multiple load zones. An integer optimization problem is formulated to find the optimal number and duration of planned…

Optimization and Control · Mathematics 2018-10-23 Atif Maqsood , Yu Zhang , Keith Corzine

Given a matrix $A$ and vector $b$ with polynomial entries in $d$ real variables $\delta=(\delta_1,\ldots,\delta_d)$ we consider the following notion of feasibility: the pair $(A,b)$ is locally feasible if there exists an open neighborhood…

Data Structures and Algorithms · Computer Science 2023-05-11 Guy Bresler , Chenghao Guo , Yury Polyanskiy

Consider positive integral solutions $x \in \mathbb{Z}^{n+1}$ to the equation $a_0 x_0 + \ldots + a_n x_n = t$. In the so called unbounded subset sum problem, the objective is to decide whether such a solution exists, whereas in the…

Data Structures and Algorithms · Computer Science 2021-08-13 Kim-Manuel Klein

We study integer programming instances over polytopes P(A,b)={x:Ax<=b} where the constraint matrix A is random, i.e., its entries are i.i.d. Gaussian or, more generally, its rows are i.i.d. from a spherically symmetric distribution. The…

Data Structures and Algorithms · Computer Science 2013-08-27 Karthekeyan Chandrasekaran , Santosh Vempala

We consider the problem of minimizing a linear function over an affine section of the cone of positive semidefinite matrices, with the additional constraint that the feasible matrix has prescribed rank. When the rank constraint is active,…

Systems and Control · Computer Science 2016-11-22 Simone Naldi
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