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An algorithm is proposed for solving optimization problems with stochastic objective and deterministic equality and inequality constraints. This algorithm is objective-function-free in the sense that it only uses the objective's gradient…

Optimization and Control · Mathematics 2026-04-01 S. Gratton , Ph. L. Toint

Studies regarding the computation of Optimal Control Problems (OCPs) with terminal inequality constraint, under the frame of the Variation Evolving Method (VEM), are carried out. The attributes of equality constraints and inequality…

Systems and Control · Computer Science 2018-01-24 Sheng Zhang , Yan-Qing Chenq , Wei-Qi Qian

In this work, we concern with the high order numerical methods for coupled forward-backward stochastic differential equations (FBSDEs). Based on the FBSDEs theory, we derive two reference ordinary differential equations (ODEs) from the…

Numerical Analysis · Mathematics 2014-03-27 Weidong Zhao , Yu Fu , Tao Zhou

In this paper we consider the problem of computing control invariant sets for linear controlled high-dimensional systems with constraints on the input and on the states. Set inclusions conditions for control invariance are presented that…

Systems and Control · Computer Science 2018-10-25 Mirko Fiacchini , Mazen Alamir

We consider stochastic algorithms derived from methods for solving deterministic optimization problems, especially comparison-based algorithms derived from stochastic approximation algorithms with a constant step-size. We develop a…

Optimization and Control · Mathematics 2022-01-03 Youhei Akimoto , Anne Auger , Nikolaus Hansen

Given a set of n points in the plane, each point having a positive weight, and an integer k>0, we present an optimal O(n \log n)-time deterministic algorithm to compute a step function with k steps that minimizes the maximum weighted…

Data Structures and Algorithms · Computer Science 2012-10-12 Hervé Fournier , Antoine Vigneron

We address the challenge of optimizing meta-parameters (hyperparameters) in machine learning, a key factor for efficient training and high model performance. Rather than relying on expensive meta-parameter search methods, we introduce…

Machine Learning · Computer Science 2025-07-10 Arsalan Sharifnassab , Saber Salehkaleybar , Richard Sutton

We establish essentially optimal bounds on the complexity of initial-value problems in the randomized and quantum settings. For this purpose we define a sequence of new algorithms whose error/cost properties improve from step to step. These…

Quantum Physics · Physics 2007-05-23 Boleslaw Kacewicz

A step-search sequential quadratic programming method is proposed for solving nonlinear equality constrained stochastic optimization problems. It is assumed that constraint function values and derivatives are available, but only stochastic…

Optimization and Control · Mathematics 2024-10-08 Albert S. Berahas , Miaolan Xie , Baoyu Zhou

- In this paper we introduce a new method to solve fixed-delay optimal control problems which exploits numerical homotopy procedures. It is known that solving this kind of problems via indirect methods is complex and computationally…

Optimization and Control · Mathematics 2017-03-16 Riccardo Bonalli , Bruno Hérissé , Emmanuel Trélat

We consider quadrature formulas of high order in time based on Radau-type, L-stable implicit Runge-Kutta schemes to solve time dependent stiff PDEs. Instead of solving a large nonlinear system of equations, we develop a method that performs…

Numerical Analysis · Mathematics 2016-04-04 Max Duarte , Matthew Emmett

Optimal block designs in small blocks are explored when the treatments have a natural ordering and interest lies in comparing consecutive pairs of treatments. We first develop an approximate theory which leads to a convenient multiplicative…

Statistics Theory · Mathematics 2014-05-20 S. Huda , Rahul Mukerjee

Integral deferred correction (IDC) methods have been shown to be an efficient way to achieve arbitrary high order accuracy and possess good stability properties. In this paper, we construct high order operator splitting schemes using the…

Numerical Analysis · Mathematics 2015-05-20 Andrew J. Christlieb , Yuan Liu , Zhengfu Xu

The purpose of this paper is concerned with the approximate solution of split equality problems. We introduce two types of algorithms and a new self-adaptive stepsize without prior knowledge of operator norms. The corresponding strong…

Functional Analysis · Mathematics 2024-09-10 Songxiao Li , Bing Tan , Zheng Zhou

An efficient approximate version of implicit Taylor methods for initial-value problems of systems of ordinary differential equations (ODEs) is introduced. The approach, based on an approximate formulation of Taylor methods, produces a…

Numerical Analysis · Mathematics 2024-02-05 Antonio Baeza , Raimund Bürger , María del Carmen Martí , Pep Mulet , David Zorío

This paper addresses the training of Neural Ordinary Differential Equations (neural ODEs), and in particular explores the interplay between numerical integration techniques, stability regions, step size, and initialization techniques. It is…

Machine Learning · Computer Science 2024-08-07 Theodor Westny , Arman Mohammadi , Daniel Jung , Erik Frisk

In a previous paper, an implementable algorithm was introduced to compute discrete solutions of sweeping processes (i.e. specific first order differential inclusions). The convergence of this numerical scheme was proved thanks to…

Numerical Analysis · Mathematics 2014-03-31 Frederic Bernicot , Juliette Venel

We review recent results obtained to solve fractional order optimal control problems with free terminal time and a dynamic constraint involving integer and fractional order derivatives. Some particular cases are studied in detail. A…

Optimization and Control · Mathematics 2013-06-04 Shakoor Pooseh , Ricardo Almeida , Delfim F. M. Torres

In this paper we propose an algorithm for the numerical solution of arbitrary differential equations of fractional order. The algorithm is obtained by using the following decomposition of the differential equation into a system of…

Numerical Analysis · Mathematics 2025-10-20 Leszczynski Jacek , Ciesielski Mariusz

Mathematical programs with or-constraints form a new class of disjunctive optimization problems with inherent practical relevance. In this paper, we provide a comparison of three different first-order methods for the numerical treatment of…

Optimization and Control · Mathematics 2019-05-07 Patrick Mehlitz