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We analyze the adaptive first order algorithm AMSGrad, for solving a constrained stochastic optimization problem with a weakly convex objective. We prove the $\mathcal{\tilde O}(t^{-1/4})$ rate of convergence for the norm of the gradient of…

Machine Learning · Statistics 2020-06-12 Ahmet Alacaoglu , Yura Malitsky , Volkan Cevher

We analyze the continuum limit of a thresholding algorithm for motion by mean curvature of one dimensional interfaces in various space-time discrete regimes. The algorithm can be viewed as a time-splitting scheme for the Allen-Cahn equation…

Analysis of PDEs · Mathematics 2014-11-04 Oleksandr Misiats , Nung Kwan Yip

A nonlinear fourth-order parabolic equation in one space dimension with periodic boundary conditions is studied. This equation arises in the context of fluctuations of a stationary nonequilibrium interface and in the modeling of quantum…

Analysis of PDEs · Mathematics 2007-05-23 J. Dolbeault , I. Gentil , A. Jungel

In this article we study the possibilities of recovering the structure of port-Hamiltonian systems starting from ``unlabelled'' ordinary differential equations describing mechanical systems. The algorithm we suggest solves the problem in…

Computational Engineering, Finance, and Science · Computer Science 2023-04-26 Vladimir Salnikov , Antoine Falaize , Daria Loziienko

We develop a new boundary condition for the weak inverse mean curvature flow, which gives canonical and non-trivial solutions in bounded domains. Roughly speaking, the boundary of the domain serves as an outer obstacle, and the evolving…

Differential Geometry · Mathematics 2025-02-10 Kai Xu

This paper addresses the problems of disparity and optical flow partitioning based on the brightness invariance assumption. We investigate new variational approaches to these problems with Potts priors and possibly box constraints. For the…

Numerical Analysis · Mathematics 2015-01-16 Xiaohao Cai , Jan Henrik Fitschen , Mila Nikolova , Gabriele Steidl , Martin Storath

This paper is concerned with a semiparametric partially linear regression model with unknown regression coefficients, an unknown nonparametric function for the non-linear component, and unobservable Gaussian distributed random errors. We…

Statistics Theory · Mathematics 2016-08-16 Irène Gannaz

In this paper, we investigate two hyperbolic flows obtained by adding forcing terms in direction of the position vector to the hyperbolic mean curvature flows in \cite{klw,hdl}. For the first hyperbolic flow, as in \cite{klw}, by using…

Differential Geometry · Mathematics 2012-11-26 Jing Mao

The famous thresholding scheme by Merriman, Bence, and Osher (Motion of multiple junctions: A level set approach. Journal of Computational Physics 112.2 (1994): 334-363.) proved itself as a very efficient time discretization of mean…

Analysis of PDEs · Mathematics 2025-08-13 Fabius Krämer

We assess the applicability and efficiency of time-adaptive high-order splitting methods applied for the numerical solution of (systems of) nonlinear parabolic problems under periodic boundary conditions. We discuss in particular several…

Numerical Analysis · Mathematics 2016-09-08 Winfried Auzinger , Othmar Koch , Michael Quell

We propose a fast and scalable optimization method to solve chance or probabilistic constrained optimization problems governed by partial differential equations (PDEs) with high-dimensional random parameters. To address the critical…

Optimization and Control · Mathematics 2020-11-20 Peng Chen , Omar Ghattas

We consider the asymptotic behaviour of small-amplitude gravity water waves in a rectangular domain where the water depth is much smaller than the horizontal scale. The control acts on one lateral boundary, by imposing the horizontal…

Analysis of PDEs · Mathematics 2021-04-02 Pei Su

Structurally stable (rough) flows on surfaces have only finitely many singularities and finitely many closed orbits, all of which are hyperbolic, and they have no trajectories joining saddle points. The violation of the last property leads…

Dynamical Systems · Mathematics 2017-06-07 Vladislav Kruglov , Dmitry Malyshev , Olga Pochinka

A method for approximating sixth-order ordinary differential equations is proposed, which utilizes a deep learning feedforward artificial neural network, referred to as a neural solver. The efficacy of this unsupervised machine learning…

Numerical Analysis · Mathematics 2025-09-16 Janavi Bhalala , B. Veena S. N. Rao

In this paper, we propose an unfitted finite element method to solve PDE-constrained shape optimization problems via shape gradient flow. The shape gradient flow system consists of the state equation, the adjoint equation, the velocity…

Numerical Analysis · Mathematics 2026-04-13 Wei Gong , Chuwen Ma , Ziyi Zhang

This work develops novel energy-stable parametric finite element methods (ES-PFEM) for the Willmore flow and curvature-dependent geometric gradient flows of surfaces in three dimensions. The key to achieving the energy stability lies in the…

Numerical Analysis · Mathematics 2025-10-06 Weizhu Bao , Yifei Li , Dongmin Wang

In this paper, we consider the online problem of scheduling independent jobs \emph{non-preemptively} so as to minimize the weighted flow-time on a set of unrelated machines. There has been a considerable amount of work on this problem in…

Data Structures and Algorithms · Computer Science 2018-04-24 Giorgio Lucarelli , Benjamin Moseley , Nguyen Kim Thang , Abhinav Srivastav , Denis Trystram

We present and experimentally realize a quantum algorithm for efficiently solving the following problem: given an $N\times N$ matrix $\mathcal{M}$, an $N$-dimensional vector $\textbf{\emph{b}}$, and an initial vector $\textbf{\emph{x}}(0)$,…

We develop an \textit{a posteriori} error analysis for a numerical estimate of the time at which a functional of the solution to a partial differential equation (PDE) first achieves a threshold value on a given time interval. This quantity…

Numerical Analysis · Mathematics 2022-06-09 Jehanzeb Chaudhry , Don Estep , Trevor Giannini , Zachary Stevens , Simon Tavener

A new class of integro-partial differential equation models is derived for the prediction of granular flow dynamics. These models are obtained using a novel limiting averaging method (inspired by techniques employed in the derivation of…

Chaotic Dynamics · Physics 2015-06-26 Denis Blackmore , Roman Samulyak , Anthony Rosato