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We introduce a simple, rigorous, and unified framework for solving nonlinear partial differential equations (PDEs), and for solving inverse problems (IPs) involving the identification of parameters in PDEs, using the framework of Gaussian…

Numerical Analysis · Mathematics 2021-08-12 Yifan Chen , Bamdad Hosseini , Houman Owhadi , Andrew M Stuart

Kernel methods are powerful tools in various data analysis tasks. Yet, in many cases, their time and space complexity render them impractical for large datasets. Various kernel approximation methods were proposed to overcome this issue,…

Machine Learning · Computer Science 2022-05-24 Roy Mitz , Yoel Shkolnisky

We propose a practical inexact augmented Lagrangian method (iALM) for nonconvex problems with nonlinear constraints. We characterize the total computational complexity of our method subject to a verifiable geometric condition, which is…

Optimization and Control · Mathematics 2022-04-22 Mehmet Fatih Sahin , Armin Eftekhari , Ahmet Alacaoglu , Fabian Latorre , Volkan Cevher

Based the homogeneous balance method, a general method is suggested to obtain several kinds of exact solutions for some kinds of nonlinear equations. The validity and reliability of the method are tested by applying it to the Bousseneq…

Chaotic Dynamics · Physics 2007-05-23 Yang lei , Zhu zhengang , Wang yinghai

We give the first algorithm for kernel Nystr\"om approximation that runs in *linear time in the number of training points* and is provably accurate for all kernel matrices, without dependence on regularity or incoherence conditions. The…

Machine Learning · Computer Science 2017-11-06 Cameron Musco , Christopher Musco

Superlinear convergence has been an elusive goal for black-box nonsmooth optimization. Even in the convex case, the subgradient method is very slow, and while some cutting plane algorithms, including traditional bundle methods, are popular…

Optimization and Control · Mathematics 2019-07-30 Adrian Lewis , Calvin Wylie

We resolve a longstanding open problem in the computational modeling of nonlinear plates by introducing a numerical method that exactly enforces the isometry constraint, namely, that the first fundamental form of the mid-surface coincides…

Numerical Analysis · Mathematics 2026-05-11 Brendan Keith , Frédéric Marazzato

We present global convergence rates for a line-search method which is based on random first-order models and directions whose quality is ensured only with certain probability. We show that in terms of the order of the accuracy, the…

Optimization and Control · Mathematics 2017-01-06 Coralia Cartis , Katya Scheinberg

We introduce the Local Increasing Regularity Method (LIRM) which allows us to get from \emph{local} a priori estimates, on solutions $u$ of a linear equation $\displaystyle Du=\omega ,$ \emph{global} ones. As an application we shall prove…

Analysis of PDEs · Mathematics 2019-11-06 Eric Amar

The general conditions under which the quadratic, uniform and monotonic convergence in the quasilinearization method of solving nonlinear ordinary differential equations could be proved are formulated and elaborated. The generalization of…

Computational Physics · Physics 2009-11-07 V. B. Mandelzweig , F. Tabakin

In this paper, we prove the global existence of weak solutions to the non-isothermal nematic liquid crystal system on $\mathbb T^2$, based on a new approximate system which is different from the classical Ginzburg-Landau approximation.…

Analysis of PDEs · Mathematics 2013-10-29 Jinkai Li , Zhouping Xin

In this work, an efficient approximation scheme has been proposed for getting accurate approximate solution of nonlinear partial differential equations with constant or variable coefficients satisfying initial conditions in a series of…

Analysis of PDEs · Mathematics 2020-09-04 Prakash Kumar Das , M. M. Panja

In this paper, two numerical approaches based on the Newton iteration method with spectral algorithms are introduced to solve the Thomas-Fermi equation. That Thomas-Fermi equation is a nonlinear singular ordinary differential equation (ODE)…

This paper extends the SQP-approach of the well-known bundle-Newton method for nonsmooth unconstrained minimization to the nonlinearly constrained case. Instead of using a penalty function or a filter or an improvement function to deal with…

Optimization and Control · Mathematics 2015-06-29 Hannes Fendl , Hermann Schichl

We develop a new multiscale finite element method for Laplace equation with oscillating Neumann boundary conditions on rough boundaries. The key point is the introduction of a new boundary condition that incorporates both the…

Numerical Analysis · Mathematics 2016-08-12 P. B. Ming , X. Xu

Second-order optimization approaches like the generalized Gauss-Newton method are considered more powerful as they utilize the curvature information of the objective function with preconditioning matrices. Albeit offering tempting…

Machine Learning · Computer Science 2024-02-06 Yongchang Hao , Yanshuai Cao , Lili Mou

We present simple, user-friendly bounds for the expected operator norm of a random kernel matrix under general conditions on the kernel function $k(\cdot,\cdot)$. Our approach uses decoupling results for U-statistics and the non-commutative…

Machine Learning · Statistics 2025-11-07 Chiraag Kaushik , Justin Romberg , Vidya Muthukumar

We give applications of known and new Liouville type theorems to universal singularity and decay estimates for non scale invariant elliptic problems, including Lane-Emden and Schr\"odinger type systems. This applies to various classes of…

Analysis of PDEs · Mathematics 2025-04-30 Pavol Quittner , Philippe Souplet

We present a new method to solve nonlinear Hammerstein equations with weakly singular kernels. The process to approximate the solution, followed usually, consists in adapting the discretization scheme from the linear case in order to obtain…

Numerical Analysis · Mathematics 2016-04-05 Laurence Grammont , Hanane Kaboul

This paper discusses the solution of nonlinear integral equations with noisy integral kernels as they appear in nonparametric instrumental regression. We propose a regularized Newton-type iteration and establish convergence and convergence…

Numerical Analysis · Mathematics 2015-04-01 Fabian Dunker , Jean-Pierre Florens , Thorsten Hohage , Jan Johannes , Enno Mammen