English
Related papers

Related papers: Computing the Least Fixed Point of Positive Polyno…

200 papers

Consider a degree-$d$ polynomial $f(\xi_1,\dots,\xi_n)$ of independent Rademacher random variables $\xi_1,\dots,\xi_n$. To what extent can $f(\xi_1,\dots,\xi_n)$ concentrate on a single point? This is the so-called polynomial…

Combinatorics · Mathematics 2025-05-30 Zhihan Jin , Matthew Kwan , Lisa Sauermann , Yiting Wang

A matrix optimization problem over an uncertain linear system on finite horizon (abbreviated as MOPUL) is studied, in which the uncertain transition matrix is regarded as a decision variable. This problem is in general NP-hard. By using the…

Optimization and Control · Mathematics 2023-10-31 Jintao Xu , Shu-Cherng Fang , Wenxun Xing

The nonnegative and positive semidefinite (PSD-) ranks are closely connected to the nonnegative and positive semidefinite extension complexities of a polytope, which are the minimal dimensions of linear and SDP programs which represent this…

Computational Complexity · Computer Science 2017-04-24 Andrii Riazanov , Mikhail Vyalyiy

We consider incomplete exponential sums in several variables of the form S(f,n,m) = \frac{1}{2^n} \sum_{x_1 \in \{-1,1\}} ... \sum_{x_n \in \{-1,1\}} x_1 ... x_n e^{2\pi i f(x)/p}, where m>1 is odd and f is a polynomial of degree d with…

Number Theory · Mathematics 2010-11-16 Eduardo Duenez , Steven J. Miller , Howard Straubing , Amitabha Roy

We provide a new proof of ``most" cases of the polynomial Wiener-Wintner theorem for $\sigma$-finite spaces, using hard-analytic methods. Specifically, we prove that whenever $(X,\mu,T)$ is a $\sigma$-finite measure-preserving system, and…

Dynamical Systems · Mathematics 2025-11-05 Ben Krause

Quadratically constrained quadratic programs (QCQPs) have a wide range of applications in signal processing and wireless communications. Non-convex QCQPs are NP-hard in general. Existing approaches relax the non-convexity using…

Optimization and Control · Mathematics 2015-06-23 Omar Mehanna , Kejun Huang , Balasubramanian Gopalakrishnan , Aritra Konar , Nicholas D. Sidiropoulos

Finding feasible points for which the proof succeeds is a critical issue in safe Branch and Bound algorithms which handle continuous problems. In this paper, we introduce a new strategy to compute very accurate approximations of feasible…

Numerical Analysis · Computer Science 2008-07-16 Alexandre Goldsztejn , Yahia Lebbah , Claude Michel , Michel Rueher

In this work, we consider the proportion of smooth (free of large prime factors) values of a binary form $F(X_1,X_2)\in\Z[X_1,X_2]$. In a particular case, we give an asymptotic equivalent for this proportion which depends on $F$. This is…

Cryptography and Security · Computer Science 2014-03-13 Razvan Barbulescu , Armand Lachand

Let $V\subset\R^m$ be a convex body, symmetric about all coordinate hyperplanes, and let $\PP_{aV},\, a\ge 0$, be a set of all algebraic polynomials whose Newton polyhedra are subsets of $aV$. We prove a limit equality as $a\to \iy$ between…

Classical Analysis and ODEs · Mathematics 2022-12-26 Michael Ganzburg

We propose a novel algorithm, termed soft quasi-Newton (soft QN), for optimization in the presence of bounded noise. Traditional quasi-Newton algorithms are vulnerable to such perturbations. To develop a more robust quasi-Newton method, we…

Optimization and Control · Mathematics 2024-03-06 Erik Berglund , Jiaojiao Zhang , Mikael Johansson

In [19], a general, inexact, efficient proximal quasi-Newton algorithm for composite optimization problems has been proposed and a sublinear global convergence rate has been established. In this paper, we analyze the convergence properties…

Numerical Analysis · Computer Science 2017-10-18 Hiva Ghanbari , Katya Scheinberg

In this paper, we study a class of fractional semi-infinite polynomial programming (FSIPP) problems, in which the objective is a fraction of a convex polynomial and a concave polynomial, and the constraints consist of infinitely many convex…

Optimization and Control · Mathematics 2021-05-18 Feng Guo , Liguo Jiao

The aim of this paper is to introduce a new Newton-type iterative method and then to show that this process converges to the unique solution of the scalar nonlinear equation f(x)=0 under weaker conditions involving only f and f' by fixed…

General Mathematics · Mathematics 2017-06-27 Nazli Karaca , Isa Yildirim

We consider the problem of maximizing a non-negative submodular set function $f:2^N \rightarrow \mathbb{R}_+$ over a ground set $N$ subject to a variety of packing type constraints including (multiple) matroid constraints, knapsack…

Discrete Mathematics · Computer Science 2014-08-14 Chandra Chekuri , Jan Vondrák , Rico Zenklusen

In this paper, we consider the optimization problem Submodular Cover (SCP), which is to find a minimum cardinality subset of a finite universe $U$ such that the value of a submodular function $f$ is above an input threshold $\tau$. In…

Data Structures and Algorithms · Computer Science 2023-09-27 Wenjing Chen , Victoria G. Crawford

The best uniform polynomial approximation of the checkmark function $f(x)=|x-\alpha |$ is considered, as $\alpha$ varies in $(-1,1)$. For each fixed degree $n$, the minimax error $E_n (\alpha)$ is shown to be piecewise analytic in $\alpha$.…

Classical Analysis and ODEs · Mathematics 2022-01-19 Peter D. Dragnev , Alan R. Legg , Ramon Orive

We propose a parallel stochastic Newton method (PSN) for minimizing unconstrained smooth convex functions. We analyze the method in the strongly convex case, and give conditions under which acceleration can be expected when compared to its…

Numerical Analysis · Mathematics 2017-05-19 Mojmír Mutný , Peter Richtárik

Let a polytope $P$ be defined by a system $A x \leq b$. We consider the problem of counting the number of integer points inside $P$, assuming that $P$ is $\Delta$-modular, where the polytope $P$ is called $\Delta$-modular if all the rank…

Computational Complexity · Computer Science 2023-05-09 D. V. Gribanov , D. S. Malyshev

We consider semidefinite programs (SDPs) of size n with equality constraints. In order to overcome scalability issues, Burer and Monteiro proposed a factorized approach based on optimizing over a matrix Y of size $n$ by $k$ such that $X =…

Machine Learning · Statistics 2018-11-29 Thomas Pumir , Samy Jelassi , Nicolas Boumal

Our contribution in this paper is two folded. We consider first the case of linear programming with real coefficients and give a method which allows the computation of a new upper bound on the distance from the origin to a feasible point.…

Optimization and Control · Mathematics 2020-10-30 Beniamin Costandin , Marius Costandin , Petru Dobra