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We derive a mixed integer nonlinear programming formulation for the problem of finding a convex polygon with a given number of vertices that is small (diameter at most one) and has maximum perimeter. The formulation is based on a geometric…

Optimization and Control · Mathematics 2024-04-03 Bernd Mulansky , Andreas Potschka

The main result of the paper is the first polynomial-time algorithm for ranking bracelets. The time-complexity of the algorithm is O(k^2 n^4), where k is the size of the alphabet and n is the length of the considered bracelets. The key part…

Combinatorics · Mathematics 2021-04-13 Duncan Adamson , Argyrios Deligkas , Vladimir V. Gusev , Igor Potapov

We study the problem of learning a partially observed matrix under the low rank assumption in the presence of fully observed side information that depends linearly on the true underlying matrix. This problem consists of an important…

Machine Learning · Statistics 2026-02-05 Dimitris Bertsimas , Nicholas A. G. Johnson

We investigate the complexity of several fundamental polynomial-time solvable problems on graphs and on matrices, when the given instance has low treewidth; in the case of matrices, we consider the treewidth of the graph formed by non-zero…

Data Structures and Algorithms · Computer Science 2015-11-05 Fedor V. Fomin , Daniel Lokshtanov , Michał Pilipczuk , Saket Saurabh , Marcin Wrochna

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

The standard coherence criterion for lower previsions is expressed using an infinite number of linear constraints. For lower previsions that are essentially defined on some finite set of gambles on a finite possibility space, we present a…

Artificial Intelligence · Computer Science 2012-03-19 Erik Quaeghebeur

Consider nonzero vectors $a_{1},\dots,a_{n}\in\mathbb{C}^{k}$, independent Rademacher random variables $\xi_{1},\dots,\xi_{n}$, and a set $S\subseteq\mathbb{C}^{k}$. What upper bounds can we prove on the probability that the random sum…

Combinatorics · Mathematics 2025-06-02 Alexandr Grebennikov , Matthew Kwan

We propose a symbolic-numeric algorithm to count the number of solutions of a polynomial system within a local region. More specifically, given a zero-dimensional system $f_1=\cdots=f_n=0$, with $f_i\in\mathbb{C}[x_1,\ldots,x_n]$, and a…

Symbolic Computation · Computer Science 2017-12-18 Ruben Becker , Michael Sagraloff

Lattices are a popular field of study in mathematical research, but also in more practical areas like cryptology or multiple-input/multiple-output (MIMO) transmission. In mathematical theory, most often lattices over real numbers are…

Information Theory · Computer Science 2022-08-19 Sebastian Stern , Cong Ling , Robert F. H. Fischer

In this paper, an exact algorithm in polynomial time is developed to solve unrestricted binary quadratic programs. The computational complexity is $O\left( n^{\frac{15}{2}}\right) $, although very conservative, it is sufficient to prove…

Data Structures and Algorithms · Computer Science 2021-02-02 Juan Ignacio Mulero-Martínez

Low-rank matrix factorizations are a class of linear models widely used in various fields such as machine learning, signal processing, and data analysis. These models approximate a matrix as the product of two smaller matrices, where the…

Machine Learning · Computer Science 2024-12-10 Olivier Vu Thanh

In this short note we give incremental algorithms for the following lattice problems: finding a basis of a lattice, computing the successive minima, and determining the orthogonal decomposition. We prove an upper bound for the number of…

Number Theory · Mathematics 2007-05-23 Boris Hemkemeier , Frank Vallentin

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

Unlike the matrix case, computing low-rank approximations of tensors is NP-hard and numerically ill-posed in general. Even the best rank-1 approximation of a tensor is NP-hard. In this paper, we use convex optimization to develop…

Statistics Theory · Mathematics 2016-09-14 Anil Aswani

We study a class of projective transformations of spectraplexes associated with self-dual cones and, on this basis, propose a polynomial-time algorithm for convex feasibility problems with positive definite constraints. At each iteration of…

Optimization and Control · Mathematics 2025-06-19 Sergei Chubanov

In this paper, we will show that the width of simplices defined by systems of linear inequalities can be computed in polynomial time if some minors of their constraint matrices are bounded. Additionally, we present some…

Optimization and Control · Mathematics 2022-11-30 D. V. Gribanov , A. Y. Chirkov

We consider the problem of finding patrol schedules for $k$ robots to visit a given set of $n$ sites in a metric space. Each robot has the same maximum speed and the goal is to minimize the weighted maximum latency of any site, where the…

Data Structures and Algorithms · Computer Science 2020-07-15 Peyman Afshani , Mark De Berg , Kevin Buchin , Jie Gao , Maarten Loffler , Amir Nayyeri , Benjamin Raichel , Rik Sarkar , Haotian Wang , Hao-Tsung Yang

We consider the following problem about dispersing points. Given a set of points in the plane, the task is to identify whether by moving a small number of points by small distance, we can obtain an arrangement of points such that no pair of…

Computational Geometry · Computer Science 2023-08-15 Fedor V. Fomin , Petr A. Golovach , Tanmay Inamdar , Saket Saurabh , Meirav Zehavi

We study the design of fixed-parameter algorithms for problems already known to be solvable in polynomial time. The main motivation is to get more efficient algorithms for problems with unattractive polynomial running times. Here, we focus…

Computational Complexity · Computer Science 2021-01-06 Archontia C. Giannopoulou , George B. Mertzios , Rolf Niedermeier

Lie group theory states that knowledge of a $m$-parameters solvable group of symmetries of a system of ordinary differential equations allows to reduce by $m$ the number of equations. We apply this principle by finding some \emph{affine…

Symbolic Computation · Computer Science 2007-06-13 Alexandre Sedoglavic
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