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We study the general integer programming problem where the number of variables $n$ is a variable part of the input. We consider two natural parameters of the constraint matrix $A$: its numeric measure $a$ and its sparsity measure $d$. We…

Optimization and Control · Mathematics 2022-08-01 Friedrich Eisenbrand , Christoph Hunkenschröder , Kim-Manuel Klein , Martin Koutecký , Asaf Levin , Shmuel Onn

We establish the first globally convergent algorithms for computing the Kreiss constant of a matrix to arbitrary accuracy. We propose three different iterations for continuous-time Kreiss constants and analogues for discrete-time Kreiss…

Optimization and Control · Mathematics 2020-12-23 Tim Mitchell

For real symmetric and complex Hermitian Gaussian processes whose values are $d\times d$ matrices, we characterize the conditions under which the probability that at least $k$ eigenvalues collide is positive for $2\le k\le d$, and we obtain…

Probability · Mathematics 2020-06-30 Jian Song , Yimin Xiao , Wangjun Yuan

We consider about calculating $M$th moments of a given polynomial in free independent semicircular elements in free probability theory. By a naive approach, this calculation requires exponential time with respect to $M$. We explicitly give…

Operator Algebras · Mathematics 2019-01-31 Rei Mizuta

The study of solving the inverse eigenvalue problem for nonnegative matrices has been around for decades. It is clear that an inverse eigenvalue problem is trivial if the desirable matrix is not restricted to a certain structure. Provided…

Numerical Analysis · Mathematics 2014-08-13 Matthew M. Lin

We present a heuristic algorithm for solving the problem of scheduling plans of tasks. The plans are ordered vectors of tasks, and tasks are basic operations carried out by resources. Plans are tied by temporal, precedence and resource…

Artificial Intelligence · Computer Science 2021-02-09 Davide Andrea Guastella

We present a novel, global algorithm for solving polynomial multiparameter eigenvalue problems (PMEPs) by leveraging a hidden variable tensor Dixon resultant framework. Our method transforms a PMEP into one or more univariate polynomial…

Numerical Analysis · Mathematics 2025-04-01 Emil Graf , Alex Townsend

We give an effective method to compute the entropy for polynomials orthogonal on a segment of the real axis that uses as input data only the coefficients of the recurrence relation satisfied by these polynomials. This algorithm is based on…

Numerical Analysis · Mathematics 2007-05-23 V. Buyarov , J. S. Dehesa , A. Martinez-Finkelshtein , J. Sanchez-Lara

How many operations do we need on the average to compute an approximate root of a random Gaussian polynomial system? Beyond Smale's 17th problem that asked whether a polynomial bound is possible, we prove a quasi-optimal bound $\text{(input…

Numerical Analysis · Mathematics 2023-06-12 Pierre Lairez

We investigate the relationship between several enumeration complexity classes and focus in particular on problems having enumeration algorithms with incremental and polynomial delay (IncP and DelayP respectively). We show that, for some…

Computational Complexity · Computer Science 2017-07-04 Florent Capelli , Yann Strozecki

Solving polynomial eigenvalue problems with eigenvector nonlinearities (PEPv) is an interesting computational challenge, outside the reach of the well-developed methods for nonlinear eigenvalue problems. We present a natural generalization…

Numerical Analysis · Mathematics 2022-05-26 Rob Claes , Karl Meerbergen , Simon Telen

This paper deals with the problem of finding, for a given graph and a given natural number k, a subgraph of k nodes with a maximum number of edges. This problem is known as the k-cluster problem and it is NP-hard on general graphs as well…

Data Structures and Algorithms · Computer Science 2011-11-09 George B. Mertzios

Smale's 17th problem asks for an algorithm which finds an approximate zero of polynomial systems in average polynomial time (see Smale 2000). The main progress on Smale's problem is Beltr\'an-Pardo (2011) and B\"urgisser-Cucker (2010). In…

Numerical Analysis · Mathematics 2015-07-15 Diego Armentano , Carlos Beltrán , Peter Bürgisser , Felipe Cucker , Michael Shub

Techniques for the evaluation of complex polynomials with one and two variables are introduced. Polynomials arise in may areas such as control systems, image and signal processing, coding theory, electrical networks, etc., and their…

Systems and Control · Computer Science 2014-08-13 Khier Benmahammed , Saeed Badran , Bassam Kourdi

In this chapter we are examining several iterative methods for solving nonlinear eigenvalue problems. These arise in variational image-processing, graph partition and classification, nonlinear physics and more. The canonical eigenproblem we…

Numerical Analysis · Mathematics 2020-10-07 Guy Gilboa

Motivated by a connection with the factorization of multivariate polynomials, we study integral convex polytopes and their integral decompositions in the sense of the Minkowski sum. We first show that deciding decomposability of integral…

Combinatorics · Mathematics 2007-05-23 S. Gao , A. G. B. Lauder

In this work, we revisit the problem of estimating the mean and covariance of an unknown $d$-dimensional Gaussian distribution in the presence of an $\varepsilon$-fraction of adversarial outliers. The pioneering work of [DKK+16] gave a…

Data Structures and Algorithms · Computer Science 2021-10-25 Pravesh K. Kothari , Peter Manohar , Brian Hu Zhang

Random matrices arise in many mathematical contexts, and it is natural to ask about the properties that such matrices satisfy. If we choose a matrix with integer entries at random, for example, what is the probability that it will have a…

Probability · Mathematics 2008-08-15 Greg Martin , Erick B. Wong

The 17th of the problems proposed by Steve Smale for the 21st century asks for the existence of a deterministic algorithm computing an approximate solution of a system of $n$ complex polynomials in $n$ unknowns in time polynomial, on the…

Numerical Analysis · Mathematics 2011-10-26 Peter Buergisser , Felipe Cucker

Gradient-based (a.k.a. `first order') optimization algorithms are routinely used to solve large scale non-convex problems. Yet, it is generally hard to predict their effectiveness. In order to gain insight into this question, we revisit the…

Probability · Mathematics 2024-12-10 Andrea Montanari , Eliran Subag