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The paper deals with the homogenization of a linear Boltzmann equation by the means of the sigma-convergence method. Under a general deterministic assumption on the coefficients of the equation, we prove that the density of the particles…

Analysis of PDEs · Mathematics 2020-10-28 Patrick Fouegap , Rodrigue Kenne B. , Gabriel Nguetseng , David Dongo , Jean Louis Woukeng

This paper studies first order methods for solving smooth minimax optimization problems $\min_x \max_y g(x,y)$ where $g(\cdot,\cdot)$ is smooth and $g(x,\cdot)$ is concave for each $x$. In terms of $g(\cdot,y)$, we consider two settings --…

Optimization and Control · Mathematics 2019-07-03 Kiran Koshy Thekumparampil , Prateek Jain , Praneeth Netrapalli , Sewoong Oh

This paper studies the convergence of a spatial semidiscretization of a three-dimensional stochastic Allen-Cahn equation with multiplicative noise. For non-smooth initial data, the regularity of the mild solution is investigated, and an…

Numerical Analysis · Mathematics 2025-07-25 Qin Zhou , Binjie Li

Finite elasticity problems commonly include material and geometric nonlinearities and are solved using various numerical methods. However, for highly nonlinear problems, achieving convergence is relatively difficult and requires small load…

Numerical Analysis · Mathematics 2018-05-01 Yue Mei , Daniel E. Hurtado , Sanjay Pant , Ankush Aggarwal

We introduce prox-convex for minimizing $F(x)=g(x)+h(C(x))+s(R(x))$, where $g$ and $h$ are convex, $C$ and $s$ are smooth, and each component of $R$ is convex (possibly nonsmooth). Here $g$ captures general convex objectives and indicator…

Optimization and Control · Mathematics 2025-12-24 Samet Uzun , Dayou Luo , Behçet Açıkmeşe , Aleksandr Y. Aravkin

The aim of this contribution is to address the convergence study of a time and space approximation scheme for an Allen-Cahn problem with constraint and perturbed by a multiplicative noise of It\^o type. The problem is set in a bounded…

Numerical Analysis · Mathematics 2025-09-03 Caroline Bauzet , Cédric Sultan , Guy Vallet , Aleksandra Zimmermann

We are concerned with large-time behaviors of solutions for Vlasov--Navier--Stokes equations in two dimensions and Vlasov-Stokes system in three dimensions including the effect of velocity alignment/misalignment. We first revisit the…

Analysis of PDEs · Mathematics 2020-07-14 Young-Pil Choi , Kyungkeun Kang , Hwa Kil Kim , Jae-Myoung Kim

We study a spatially inhomogeneous coagulation model that contains a transport term in the spatial variable. The transport term models the vertical motion of particles due to gravity, thereby incorporating their fall into the dynamics.…

Analysis of PDEs · Mathematics 2025-10-07 Iulia Cristian , Juan J. L. Velázquez

An approach to some "optimal" (more precisely, non-improvable) regularity of solutions of the thin film equation u_{t} = -\nabla \cdot(|u|^{n} \nabla \D u) in \ren \times \re_+, u(x,0)=u_0(x) in \re^N, where n in (0,2) is a fixed exponent,…

Analysis of PDEs · Mathematics 2015-05-07 Pablo Alvarez-Caudevilla , Jonathan D. Evans , Victor A. Galaktionov

The linear convex log-homotopy has been used in the derivation of particle flow filters. One natural question is whether it is beneficial to consider other forms of homotopy. We revisit this question by considering a general linear form of…

Optimization and Control · Mathematics 2021-07-13 Liyi Dai , Frederick E. Daum

Higher-order regularization problem formulations are popular frameworks used in machine learning, inverse problems and image/signal processing. In this paper, we consider the computational problem of finding the minimizer of the Sobolev…

Numerical Analysis · Mathematics 2023-10-20 Adrien Weihs , Jalal Fadili , Matthew Thorpe

Gradient normalization and soft clipping are two popular techniques for tackling instability issues and improving convergence of stochastic gradient descent (SGD) with momentum. In this article, we study these types of methods through the…

Optimization and Control · Mathematics 2025-07-01 Måns Williamson , Tony Stillfjord

Stochastic heavy ball momentum (SHB) is commonly used to train machine learning models, and often provides empirical improvements over stochastic gradient descent. By primarily focusing on strongly-convex quadratics, we aim to better…

Optimization and Control · Mathematics 2025-06-02 Anh Dang , Reza Babanezhad , Sharan Vaswani

We propose a new algorithm that finds an $\varepsilon$-approximate fixed point of a smooth function from the $n$-dimensional $\ell_2$ unit ball to itself. We use the general framework of finding approximate solutions to a variational…

Computer Science and Game Theory · Computer Science 2025-01-22 Idan Attias , Yuval Dagan , Constantinos Daskalakis , Rui Yao , Manolis Zampetakis

We investigate the consistency and convergence of flux-corrected finite element approximations in the context of nonlinear hyperbolic conservation laws. In particular, we focus on a monolithic convex limiting approach and prove a…

Numerical Analysis · Mathematics 2023-08-30 Dmitri Kuzmin , Mária Lukácova-Medvid'ová , Philipp Öffner

We consider the spatially inhomogeneous Landau equation with initial data that is bounded by a Gaussian in the velocity variable. In the case of moderately soft potentials, we show that weak solutions immediately become smooth and remain…

Analysis of PDEs · Mathematics 2019-11-06 Christopher Henderson , Stanley Snelson

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

Consider the thin-film equation $h_t + \left(h h_{yyy}\right)_y = 0$ with a zero contact angle at the free boundary, that is, at the triple junction where liquid, gas, and solid meet. Previous results on stability and well-posedness of this…

Analysis of PDEs · Mathematics 2020-08-25 Manuel V. Gnann , Slim Ibrahim , Nader Masmoudi

The strong-form asymmetric kernel-based collocation method, commonly referred to as the Kansa method, is easy to implement and hence is widely used for solving engineering problems and partial differential equations despite the lack of…

Numerical Analysis · Mathematics 2018-01-03 Ka-Chun Cheung , Leevan Ling , Robert Schaback

This paper deals with Tikhonov regularization for linear and nonlinear ill-posed operator equations with wavelet Besov norm penalties. We show order optimal rates of convergence for finitely smoothing operators and for the backwards heat…

Numerical Analysis · Mathematics 2019-04-03 Frederic Weidling , Benjamin Sprung , Thorsten Hohage
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