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We present an algorithm based on continuation techniques that can be applied to solve numerically minimization problems with equality constraints. We focus on problems with a great number of local minima which are hard to obtain by local…

Numerical Analysis · Mathematics 2019-09-17 Elisabete Alberdi , Mikel Antoñana , Joseba Makazaga , Ander Murua

We consider stopping criteria that balance algebraic and discretization errors for the conjugate gradient algorithm applied to high-order finite element discretizations of Poisson problems. Firstly, we introduce a new stopping criterion…

Numerical Analysis · Mathematics 2024-08-06 Yichen Guo , Eric de Sturler , Tim Warburton

We study the problem of optimal subset selection from a set of correlated random variables. In particular, we consider the associated combinatorial optimization problem of maximizing the determinant of a symmetric positive definite matrix…

Computation · Statistics 2019-07-12 Yu Wang , Nhu D. Le , James V. Zidek

In this paper, we study the following robust optimization problem. Given an independence system and candidate objective functions, we choose an independent set, and then an adversary chooses one objective function, knowing our choice. Our…

Data Structures and Algorithms · Computer Science 2018-05-22 Yasushi Kawase , Hanna Sumita

A local convergence rate is established for an orthogonal collocation method based on Gauss quadrature applied to an unconstrained optimal control problem. If the continuous problem has a sufficiently smooth solution and the Hamiltonian…

Optimization and Control · Mathematics 2016-07-12 William W. Hager , Hongyan Hou , Anil V. Rao

A local convergence rate is established for an orthogonal collocation method based on Radau quadrature applied to an unconstrained optimal control problem. If the continuous problem has a sufficiently smooth solution and the Hamiltonian…

Numerical Analysis · Mathematics 2015-09-15 William W. Hager , Hongyan Hou , Anil V. Rao

In this paper, we introduce a method for approximating the solution to inference and optimization tasks in uncertain and deterministic reasoning. Such tasks are in general intractable for exact algorithms because of the large number of…

Artificial Intelligence · Computer Science 2012-12-12 David Ephraim Larkin

We present a framework for deterministically rounding a dynamic fractional matching. Applying our framework in a black-box manner on top of existing fractional matching algorithms, we derive the following new results: (1) The first…

Data Structures and Algorithms · Computer Science 2021-05-05 Sayan Bhattacharya , Peter Kiss

State-of-the-art methods for solving smooth optimization problems are nonlinear conjugate gradient, low memory BFGS, and Majorize-Minimize (MM) subspace algorithms. The MM subspace algorithm which has been introduced more recently has shown…

Optimization and Control · Mathematics 2016-08-24 Emilie Chouzenoux , Jean-Christophe Pesquet

This paper focuses on two-sided matching where one side (a hospital or firm) is matched to the other side (a doctor or worker) so as to maximize a cardinal objective under general feasibility constraints. In a standard model, even though…

Computer Science and Game Theory · Computer Science 2019-07-10 Yasushi Kawase , Atsushi Iwasaki

Joint matching over a collection of objects aims at aggregating information from a large collection of similar instances (e.g. images, graphs, shapes) to improve maps between pairs of them. Given multiple matches computed between a few…

Machine Learning · Computer Science 2015-01-06 Yuxin Chen , Leonidas J. Guibas , Qi-Xing Huang

In the Network Revenue Management (NRM) problem, products composed of up to L resources are sold to stochastically arriving customers. We take a randomized rounding approach to NRM, motivated by the modern tool of Online Contention…

Computer Science and Game Theory · Computer Science 2024-12-10 Will Ma , Calum MacRury , Jingwei Zhang

We propose an exact polynomial algorithm for a resource allocation problem with convex costs and constraints on partial sums of resource consumptions, in the presence of either continuous or integer variables. No assumption of strict…

Data Structures and Algorithms · Computer Science 2014-04-29 Thibaut Vidal , Patrick Jaillet , Nelson Maculan

We consider stochastic variational inequality problems where the mapping is monotone over a compact convex set. We present two robust variants of stochastic extragradient algorithms for solving such problems. Of these, the first scheme…

Optimization and Control · Mathematics 2014-03-25 Farzad Yousefian , Angelia Nedic , Uday V. Shanbhag

The (constrained) minimization of a ratio of set functions is a problem frequently occurring in clustering and community detection. As these optimization problems are typically NP-hard, one uses convex or spectral relaxations in practice.…

Machine Learning · Statistics 2013-06-17 Thomas Bühler , Syama Sundar Rangapuram , Simon Setzer , Matthias Hein

In combinatorial optimization, partial variable assignments are called persistent if they agree with some optimal solution. We propose persistency criteria for the multicut and max-cut problem as well as fast combinatorial routines to…

Optimization and Control · Mathematics 2018-12-05 Jan-Hendrik Lange , Bjoern Andres , Paul Swoboda

In this paper, approximation schemes are proposed for handling load uncertainty in compliance-based topology optimization problems, where the uncertainty is described in the form of a set of finitely many loading scenarios. Efficient…

Computational Engineering, Finance, and Science · Computer Science 2022-05-03 Mohamed Tarek , Tapabrata Ray

This paper considers master equations for Markovian kinetic schemes that possess the detailed balance property. Chemical kinetics, as a prime example, often yields large-scale, highly stiff equations. Based on chemical intuitions, Sumiya et…

Numerical Analysis · Mathematics 2023-12-12 Satoru Iwata , Taihei Oki , Shinsaku Sakaue

Efficient methods to provide sub-optimal solutions to non-convex optimization problems with knowledge of the solution's sub-optimality would facilitate the widespread application of nonlinear optimal control algorithms. To that end,…

Optimization and Control · Mathematics 2023-04-10 Prithvi Akella , Aaron D. Ames

Mathematical Selection is a method in which we select a particular choice from a set of such. It have always been an interesting field of study for mathematicians. Accordingly, Combinatorial Optimization is a sub field of this domain of…

Computational Complexity · Computer Science 2023-06-29 Anurag Dutta , K. Lakshmanan , A. Ramamoorthy , Liton Chandra Voumik , John Harshith , John Pravin Motha
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