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This article describes a novel approach to chance-constrained programming based on the sample average approximation (SAA) method. Recent work focuses on heuristic approximations to the SAA problem and we introduce a novel approach which…

Optimization and Control · Mathematics 2023-07-25 Rick Jeuken , Michael Forbes

The PSA system commonly used in the context of gas-solid chromatography is reformulated as a single kinetic equation using an additional kinetic variable. A kinetic numerical scheme is built from this new formulation and its behavior is…

Analysis of PDEs · Mathematics 2017-02-21 C Bourdarias , M Gisclon , Stéphane Junca

Giving a new form of the vortex mode equation by a proper change of parameter, our aim is to analyze the point and contact symmetries of the new equation. Fundamental invariants and a form of general solutions of point transformations along…

Differential Geometry · Mathematics 2011-12-30 Mehdi Nadjafikhah , Ali Mahdipour--Shirayeh

The solution of the continuous time filtering problem can be represented as a ratio of two expectations of certain functionals of the signal process that are parametrized by the observation path. We introduce a new time discretisation of…

Probability · Mathematics 2014-08-26 Dan Crisan , Salvador Ortiz-Latorre

This paper is a study on solutions of the Sample Average Approximation Method to solve compound stochastic programs. We derive nonasymptotic upper estimates for probabilities of the approximation errors. The results depend on the sample…

Optimization and Control · Mathematics 2025-08-29 Volker Kratschmer

Given an infeasible, unbounded, or pathological convex optimization problem, a natural question to ask is: what is the smallest change we can make to the problem's parameters such that the problem becomes solvable? In this paper, we address…

Optimization and Control · Mathematics 2020-01-30 Shane Barratt , Guillermo Angeris , Stephen Boyd

The paper presents a construction of a quantitative measure of variability for parameter estimates in the data fitting problem under interval uncertainty. It shows the degree of variability and ambiguity of the estimate, and the need for…

Numerical Analysis · Mathematics 2020-03-12 Sergey P. Shary

This paper considers the computer model calibration problem and provides a general frequentist solution. Under the proposed framework, the data model is semi-parametric with a nonparametric discrepancy function which accounts for any…

Methodology · Statistics 2015-09-14 Raymond K. W. Wong , Curtis B. Storlie , Thomas C. M. Lee

In this paper, we consider the Cauchy problem for the semilinear beam equation in the subcritical case. We prove an asymptotic stability result of self-similar solutions of the associated parabolic problem. The proof of our results are…

Analysis of PDEs · Mathematics 2026-05-04 Mohamed Ali Hamza , Yuta Wakasugi , Shuji Yoshikawa

In this paper we present a complete asymptotic expansion of a symmetric homogeneous stable (balanced), stabilizable and stabilized mean. By including known asymptotic expansions of parametric means it is shown how the obtained coefficients…

Classical Analysis and ODEs · Mathematics 2024-07-15 Lenka Mihoković

In this paper, we consider one-to-one matchings between two disjoint groups of agents. Each agent has a preference over a subset of the agents in the other group, and these preferences may contain ties. Strong stability is one of the…

Computer Science and Game Theory · Computer Science 2024-01-08 Naoyuki Kamiyama

In this paper, is introduced a new proposal of resolvent for equilibrium problems in terms of the Busemann's function. A great advantage of this new proposal is that, in addition to be a natural extension of the proposal in the linear…

Optimization and Control · Mathematics 2021-11-09 G. C. Bento , J. X. Cruz Neto , I. D. L. Melo

The Kaczmarz algorithm (KA) is a popular method for solving a system of linear equations. In this note we derive a new exponential convergence result for the KA. The key allowing us to establish the new result is to rewrite the KA in such a…

Systems and Control · Computer Science 2015-06-23 Liang Dai , Thomas Schön

An algorithm is proposed, analyzed, and tested experimentally for solving stochastic optimization problems in which the decision variables are constrained to satisfy equations defined by deterministic, smooth, and nonlinear functions. It is…

Optimization and Control · Mathematics 2021-07-09 Frank E. Curtis , Daniel P. Robinson , Baoyu Zhou

In this paper, we establish a globally quantitative estimate of unique continuation at one time point for solutions of parabolic equations with Neumann boundary conditions in bounded domains. Our proof is mainly based on Carleman commutator…

Analysis of PDEs · Mathematics 2022-02-22 Yueliang Duan , Lijuan Wang , Can Zhang

We present a new algorithm for solving optimization problems with objective functions that are the sum of a smooth function and a (potentially) nonsmooth regularization function, and nonlinear equality constraints. The algorithm may be…

Optimization and Control · Mathematics 2024-04-12 Yutong Dai , Xiaoyi Qu , Daniel P. Robinson

Linguistic variables represent crisp information in a form and precision appropriate for the problem. For example, to answer the question "How are you?" one may say "I am fine." the linguistic variables like "fine", so common in everyday…

Formal Languages and Automata Theory · Computer Science 2011-12-16 Supriya Raheja , Reena Dhadich , Smita Rajpal

Ten new exact solutions of the Riccati equation $dy/dx=a(x)+b(x)y+c(x)y^{2}$ are presented. The solutions are obtained by assuming certain relations among the coefficients $a(x)$, $b(x)$ and $c(x)$ of the Riccati equation, in the form of…

Classical Analysis and ODEs · Mathematics 2014-01-03 Tiberiu Harko , Francisco S. N. Lobo , M. K. Mak

This paper addresses the challenge of probabilistic parameter estimation given measurement uncertainty in real-time. We provide a general formulation and apply this to pose estimation for an autonomous visual landing system. We present…

This paper provides a new regularization method which is particularly suitable for linear exponentially ill-posed problems. Under logarithmic source conditions (which have a natural interpretation in terms of Sobolev spaces in the…

Numerical Analysis · Mathematics 2020-07-08 Walter Cedric Simo Tao Lee