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The range, segment and rectangle query problems are fundamental problems in computational geometry, and have extensive applications in many domains. Despite the significant theoretical work on these problems, efficient implementations can…

Computational Geometry · Computer Science 2018-08-08 Yihan Sun , Guy E. Blelloch

We study numerical methods for porous media equation (PME). There are two important characteristics: the finite speed propagation of the free boundary and the potential waiting time, which make the problem not easy to handle. Based on…

Numerical Analysis · Mathematics 2019-03-27 Chenghua Duan , Chun Liu , Cheng Wang , Xingye Yue

In this paper, we discuss the second-order finite element method (FEM) and finite difference method (FDM) for numerically solving elliptic cross-interface problems characterized by vertical and horizontal straight lines, piecewise constant…

Numerical Analysis · Mathematics 2024-11-04 Qiwei Feng

Synthetic Control Methods (SCMs) have become a fundamental tool for comparative case studies. The core idea behind SCMs is to estimate treatment effects by predicting counterfactual outcomes for a treated unit using a weighted combination…

Econometrics · Economics 2025-11-10 Masahiro Kato , Akari Ohda

In this paper we address the temporal energy growth associated with numerical approximations of the perfectly matched layer (PML) for Maxwell's equations in first order form. In the literature, several studies have shown that a numerical…

Numerical Analysis · Mathematics 2014-05-06 Kenneth Duru

We establish robust exponential convergence for $rp$-Finite Element Methods (FEMs) applied to fourth order singularly perturbed boundary value problems, in a \emph{balanced norm} which is stronger than the usual energy norm associated with…

Numerical Analysis · Mathematics 2023-09-20 Torsten Linß , Christos Xenophontos

This work proposes and analyzes a generalized acceleration technique for decreasing the computational complexity of using stochastic collocation (SC) methods to solve partial differential equations (PDEs) with random input data. The SC…

Numerical Analysis · Mathematics 2015-05-05 Diego Galindo , Peter Jantsch , Clayton G. Webster , Guannan Zhang

Inexact alternating direction multiplier methods (ADMMs) are developed for solving general separable convex optimization problems with a linear constraint and with an objective that is the sum of smooth and nonsmooth terms. The approach…

Optimization and Control · Mathematics 2016-04-12 William W. Hager , Hongchao Zhang

The classical Method of Successive Approximations (MSA) is an iterative method for solving stochastic control problems and is derived from Pontryagin's optimality principle. It is known that the MSA may fail to converge. Using careful…

Optimization and Control · Mathematics 2020-11-18 Bekzhan Kerimkulov , David Šiška , Łukasz Szpruch

The oversampling multiscale finite element method (MsFEM) is one of the most popular methods for simulating composite materials and flows in porous media which may have many scales. But the method may be inapplicable or inefficient in some…

Numerical Analysis · Mathematics 2012-11-16 Weibing Deng , Haijun Wu

This paper investigates an efficient exponential integrator generalized multiscale finite element method for solving a class of time-evolving partial differential equations in bounded domains. The proposed method first performs the spatial…

Numerical Analysis · Mathematics 2024-07-08 Leonardo A. Poveda , Juan Galvis , Eric Chung

Large language models (LLMs) have demonstrated remarkable performance, yet their diverse strengths and weaknesses prevent any single LLM from achieving dominance across all tasks. Ensembling multiple LLMs is a promising approach to generate…

Computation and Language · Computer Science 2025-03-17 Jiaxin Zhang , Zhuohang Li , Wendi Cui , Kamalika Das , Bradley malin , Sricharan Kumar

Sequential Monte Carlo (SMC) methods are a widely used set of computational tools for inference in non-linear non-Gaussian state-space models. We propose a new SMC algorithm to compute the expectation of additive functionals recursively.…

Methodology · Statistics 2010-12-27 Pierre Del Moral , Arnaud Doucet , Sumeetpal Singh

An inexact accelerated stochastic Alternating Direction Method of Multipliers (AS-ADMM) scheme is developed for solving structured separable convex optimization problems with linear constraints. The objective function is the sum of a…

Optimization and Control · Mathematics 2020-10-27 Jianchao Bai , William W. Hager , Hongchao Zhang

Multimodal Entity Alignment (MMEA) aims to identify equivalent entities across different data modalities, enabling structural data integration that in turn improves the performance of various large language model applications. To lift the…

Information Retrieval · Computer Science 2026-03-04 Yunpeng Hong , Chenyang Bu , Jie Zhang , Yi He , Di Wu , Xindong Wu

The Immersed Boundary method is a simple, efficient, and robust numerical scheme for solving PDE in general domains, yet for fluid problems it only achieves first-order spatial accuracy near embedded boundaries for the velocity field and…

Numerical Analysis · Mathematics 2017-03-08 David B. Stein , Robert D. Guy , Becca Thomases

We consider the problem of maximum a posteriori (MAP) inference in discrete graphical models. We present a parallel MAP inference algorithm called Bethe-ADMM based on two ideas: tree-decomposition of the graph and the alternating direction…

Artificial Intelligence · Computer Science 2013-09-27 Qiang Fu , Huahua Wang , Arindam Banerjee

We report on an improvement to the implementation of the Maximum Entropy Method (MEM). It amounts to departing from the search space obtained through a singular value decomposition (SVD) of the Kernel. Based on the shape of the SVD basis…

Computational Physics · Physics 2015-03-20 Alexander Rothkopf

(Partial) differential equations (PDEs) are fundamental tools for describing natural phenomena, making their solution crucial in science and engineering. While traditional methods, such as the finite element method, provide reliable…

Machine Learning · Computer Science 2025-03-11 Viggo Moro , Luiz F. O. Chamon

The Method of Successive Approximations (MSA) is a fixed-point iterative method used to solve stochastic optimal control problems. It is an indirect method based on the conditions derived from the Stochastic Maximum Principle (SMP), an…

Optimization and Control · Mathematics 2024-05-14 Safouane Taoufik , Badr Missaoui