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We study distributed algorithms for expected loss minimization where the datasets are large and have to be stored on different machines. Often we deal with minimizing the average of a set of convex functions where each function is the…

Machine Learning · Computer Science 2019-07-24 Samira Sheikhi

This paper offers a matrix-free first-order numerical method to solve large-scale conic optimization problems. Solving systems of linear equations pose the most computationally challenging part in both first-order and second-order numerical…

Optimization and Control · Mathematics 2022-03-11 Muhammad Adil , Ramtin Madani , Sasan Tavakkol , Ali Davoudi

We present an algorithm for computing Groebner bases of vanishing ideals of points that is optimized for the case when the number of points in the associated variety is less than the number of indeterminates. The algorithm first identifies…

Commutative Algebra · Mathematics 2007-11-26 Winfried Just , Brandilyn Stigler

A natural optimization model that formulates many online resource allocation and revenue management problems is the online linear program (LP) in which the constraint matrix is revealed column by column along with the corresponding…

Data Structures and Algorithms · Computer Science 2014-04-10 Shipra Agrawal , Zizhuo Wang , Yinyu Ye

This paper deals with exploiting symmetry for solving linear and integer programming problems. Basic properties of linear representations of finite groups can be used to reduce symmetric linear programming to solving linear programs of…

Optimization and Control · Mathematics 2015-07-31 Richard Bödi , Katrin Herr , Michael Joswig

Near-term large quantum computers are not able to operate as a single processing unit. It is therefore required to partition a quantum circuit into smaller parts, and then each part is executed on a small unit. This approach is known as…

While powerful tools have been developed to analyze quantum query complexity, there are still many natural problems that do not fit neatly into the black box model of oracles. We create a new model that allows multiple oracles with…

Quantum Physics · Physics 2016-04-12 Shelby Kimmel , Cedric Yen-Yu Lin , Han-Hsuan Lin

Minimal problems in computer vision raise the demand of generating efficient automatic solvers for polynomial equation systems. Given a polynomial system repeated with different coefficient instances, the traditional Gr\"obner basis or…

Computer Vision and Pattern Recognition · Computer Science 2020-04-27 Bo Li , Viktor Larsson

In the dynamic set cover problem, the input is a dynamic universe of elements and a fixed collection of sets. As elements are inserted or deleted, the goal is to efficiently maintain an approximate minimum set cover. While the past decade…

Data Structures and Algorithms · Computer Science 2026-04-06 Amitai Uzrad

Given a finite set of closed rational points of affine space over a field, we give a Gr\"obner basis for the lexicographic ordering of the ideal of polynomials which vanish at all given points. Our method is an alternative to the…

Commutative Algebra · Mathematics 2007-05-23 Mathias Lederer

Projection-based model reduction has become a popular approach to reduce the cost associated with integrating large-scale dynamical systems so they can be used in many-query settings such as optimization and uncertainty quantification. For…

Numerical Analysis · Mathematics 2020-08-26 Han Gao , Jian-Xun Wang , Matthew J. Zahr

In this work we address two questions concerning Grover's algorithm. In the first we give an answer to the question how to employ Grover's algorithm for actual search over database. We introduce a quantum model of an unordered phone book…

Quantum Physics · Physics 2014-06-26 Daniel Reitzner , Mario Ziman

In this note, we extend modular techniques for computing Gr\"obner bases from the commutative setting to the vast class of noncommutative $G$-algebras. As in the commutative case, an effective verification test is only known to us in the…

Rings and Algebras · Mathematics 2017-04-11 Wolfram Decker , Christian Eder , Viktor Levandovskyy , Sharwan K. Tiwari

In numerical simulations of many charged systems at the micro/nano scale, a common theme is the repeated solution of the Poisson-Boltzmann equation. This task proves challenging, if not entirely infeasible, largely due to the nonlinearity…

Numerical Analysis · Mathematics 2018-08-29 Lijie Ji , Yanlai Chen , Zhenli Xu

This is the first in a series of papers which deal with the development of novel methods for solving a system of linear algebraic equations with a time complexity lower than existing algorithms. The NxN system of linear equations, Ax = b,…

Optimization and Control · Mathematics 2022-06-16 Vilas Patwardhan

By any account, the 1998 proof of the Kepler conjecture is complex. The thesis underlying this article is that the proof is complex because it is highly under-automated. Throughout that proof, manual procedures are used where automated ones…

Metric Geometry · Mathematics 2007-05-23 Thomas C. Hales

We present a successive constraint approach that makes it possible to cheaply solve large-scale linear matrix inequalities for a large number of parameter values. The efficiency of our method is made possible by an offline/online…

Numerical Analysis · Mathematics 2017-08-08 Robert O'Connor

We describe how Groebner bases can be used to solve the reduction problem for Feynman integrals, i.e. to construct an algorithm that provides the possibility to express a Feynman integral of a given family as a linear combination of some…

High Energy Physics - Lattice · Physics 2009-11-11 A. V. Smirnov , V. A. Smirnov

We present a new open source C library \texttt{msolve} dedicated to solving multivariate polynomial systems of dimension zero through computer algebra methods. The core algorithmic framework of \texttt{msolve} relies on Gr\''obner bases and…

Symbolic Computation · Computer Science 2021-05-20 Jérémy Berthomieu , Christian Eder , Mohab Safey El Din

Genetic Programming is an evolutionary algorithm that generates computer programs, or mathematical expressions, to solve complex problems. In this Guide, we demonstrate how to use Genetic Programming to develop surrogate models to mitigate…