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We propose a random-subspace algorithmic framework for global optimization of Lipschitz-continuous objectives, and analyse its convergence using novel tools from conic integral geometry. X-REGO randomly projects, in a sequential or…

Optimization and Control · Mathematics 2021-07-28 Coralia Cartis , Estelle Massart , Adilet Otemissov

We consider a D-dimensional model of gravity with non-linear "scalar fields" as a matter source. The model is defined on the product manifold M, which contains n Einstein factor spaces. General cosmological type solutions to the field…

General Relativity and Quantum Cosmology · Physics 2015-06-04 A. A. Golubtsova , V. D. Ivashchuk

This paper deals with the equation $-\Delta u+\mu u=f$ on high-dimensional spaces $\mathbb{R}^m$, where the right-hand side $f(x)=F(Tx)$ is composed of a separable function $F$ with an integrable Fourier transform on a space of a dimension…

Numerical Analysis · Mathematics 2024-11-19 Harry Yserentant

We study the problem of covering a given set of $n$ points in a high, $d$-dimensional space by the minimum enclosing polytope of a given arbitrary shape. We present algorithms that work for a large family of shapes, provided either only…

Computational Geometry · Computer Science 2007-05-23 Rina Panigrahy

We introduce a Monte Carlo method, as a modification of existing cluster algorithms, which allows simulations directly on systems of infinite size, and for quantum models also at beta=infinity. All two-point functions can be obtained,…

Statistical Mechanics · Physics 2007-05-23 H. G. Evertz , W. von der Linden

This paper develops a mathematical theory of super-resolution. Broadly speaking, super-resolution is the problem of recovering the fine details of an object---the high end of its spectrum---from coarse scale information only---from samples…

Information Theory · Computer Science 2012-11-15 Emmanuel Candes , Carlos Fernandez-Granda

This paper considers the minimization of a general objective function $f(X)$ over the set of rectangular $n\times m$ matrices that have rank at most $r$. To reduce the computational burden, we factorize the variable $X$ into a product of…

Information Theory · Computer Science 2018-07-04 Zhihui Zhu , Qiuwei Li , Gongguo Tang , Michael B. Wakin

A new model of causal failure is presented and used to solve a novel replica placement problem in data centers. The model describes dependencies among system components as a directed graph. A replica placement is defined as a subset of…

Data Structures and Algorithms · Computer Science 2017-01-09 K. Alex Mills , R. Chandrasekaran , Neeraj Mittal

Suppose $A \in \mathbb{R}^{n \times n}$ is invertible and we are looking for the solution of $Ax = b$. Given an initial guess $x_1 \in \mathbb{R}$, we show that by reflecting through hyperplanes generated by the rows of $A$, we can generate…

Numerical Analysis · Mathematics 2021-09-22 Stefan Steinerberger

We study functions $f : [0, 1]^d \rightarrow [0, 1]^d$ that are both monotone and contracting, and we consider the problem of finding an $\varepsilon$-approximate fixed point of $f$. We show that the problem lies in the complexity class…

Computational Complexity · Computer Science 2025-03-28 Eleni Batziou , John Fearnley , Spencer Gordon , Ruta Mehta , Rahul Savani

Functional iterations such as Newton's are a popular tool for polynomial root-finding. We consider realistic situation where some (e.g., better-conditioned) roots have already been approximated and where further computations is directed to…

Numerical Analysis · Mathematics 2019-07-09 Remi Imbach , Victor Y. Pan , Chee Yap , Ilias S. Kotsireas , Vitaly Zaderman

Suppose $p$ is a prime, $t$ is a positive integer, and $f\!\in\!\mathbb{Z}[x]$ is a univariate polynomial of degree $d$ with coefficients of absolute value $<\!p^t$. We show that for any fixed $t$, we can compute the number of roots in…

Number Theory · Mathematics 2019-02-13 Qi Cheng , Shuhong Gao , J. Maurice Rojas , Daqing Wan

Monte Carlo Tree Search is a popular method for solving decision making problems. Faster implementations allow for more simulations within the same wall clock time, directly improving search performance. To this end, we present an…

Artificial Intelligence · Computer Science 2025-08-29 James Ragan , Fred Y. Hadaegh , Soon-Jo Chung

A new numerical method for an inverse problem for an elliptic equation with unknown potential is proposed. In this problem the point source is running along a straight line and the source-dependent Dirichlet boundary condition is measured…

Numerical Analysis · Mathematics 2008-09-24 Hua Shan , M. V. Klibanov , Jianzhong Su , Natee Pantong , Hanli Liu

We were asked to debate the value of the cosmological mass-density parameter Omega. Is Omega_m=1 in accordance with the simplest model? Is Omega_m much smaller as indicated by some observations? There is conflicting evidence. We lay out the…

Astrophysics · Physics 2007-05-23 Avishai Dekel , David Burstein , Simon D. M. White

This paper proposes a random subspace trust-region algorithm for general convex-constrained derivative-free optimization (DFO) problems. Similar to previous random subspace DFO methods, the convergence of our algorithm requires a certain…

Optimization and Control · Mathematics 2026-05-14 Yiwen Chen , Warren Hare , Amy Wiebe

Optimal power flow (OPF) is an important problem in the operation of electric power systems. Due to the OPF problem's non-convexity, there may exist multiple local optima. Certifiably obtaining the global solution is important for certain…

Optimization and Control · Mathematics 2019-06-17 Alireza Barzegar , Daniel K. Molzahn , Rong Su

We rephrase Monge's optimal transportation (OT) problem with quadratic cost--via a Monge-Amp\`ere equation--as an infinite-dimensional optimization problem, which is in fact a convex problem when the target is a log-concave measure with…

Numerical Analysis · Mathematics 2017-08-29 Michael Lindsey , Yanir A. Rubinstein

Fast exact algorithms are known for Hamiltonian paths in undirected and directed bipartite graphs through elegant though involved algorithms that are quite different from each other. We devise algorithms that are simple and similar to each…

Data Structures and Algorithms · Computer Science 2025-12-10 V. Arvind , Srijan Chakraborty , Samir Datta , Asif Khan

In this paper, we consider lasso problems with zero-sum constraint, commonly required for the analysis of compositional data in high-dimensional spaces. A novel algorithm is proposed to solve these problems, combining a tailored active-set…

Optimization and Control · Mathematics 2022-09-26 Andrea Cristofari
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