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The paper studies a higher order unfitted finite element method for the Stokes system posed on a surface in three-dimensional space. The method employs generalized Taylor-Hood finite element pairs on tetrahedral bulk mesh to discretize the…

Numerical Analysis · Mathematics 2020-03-17 Thomas Jankuhn , Maxim A. Olshanskii , Arnold Reusken , Alexander Zhiliakov

This work proposes a basis for improved throughput of matrix-free evaluation of discontinuous Galerkin symmetric interior penalty discretizations on hexahedral elements. The basis relies on ideas of Hermite polynomials. It is used in a…

Numerical Analysis · Mathematics 2019-07-22 Martin Kronbichler , Katharina Kormann , Niklas Fehn , Peter Munch , Julius Witte

In this paper, an inexact proximal-point penalty method is studied for constrained optimization problems, where the objective function is non-convex, and the constraint functions can also be non-convex. The proposed method approximately…

Optimization and Control · Mathematics 2020-12-02 Qihang Lin , Runchao Ma , Yangyang Xu

We study a class of bilevel optimization problems in which both the upper- and lower-level problems have minimax structures. This setting captures a broad range of emerging applications. Despite the extensive literature on bilevel…

Optimization and Control · Mathematics 2026-05-11 Yiyang Shen , Yutian He , Weiran Wang , Qihang Lin

A new interior-exterior penalty method for solving quasi-variational inequality and pseudo-monotone operators arising in two-dimensional point contact problem has been analyzed and developed in discontinuous Galerkin finite volume method…

Numerical Analysis · Mathematics 2021-10-26 Peeyush Singh

In the present work, we examine and analyze an hp-version interior penalty discontinuous Galerkin finite element method for the numerical approximation of a steady fluid system on computational meshes consisting of polytopic elements on the…

Numerical Analysis · Mathematics 2024-04-26 Efthymios N. Karatzas

This article explores the estimation of precision matrices in high-dimensional Gaussian graphical models. We address the challenge of improving the accuracy of maximum likelihood-based precision estimation through penalization.…

Methodology · Statistics 2023-12-27 A. Bekker , A. Kheyri , M. Arashi

This paper aims to develop an efficient adaptive finite element method for the second-order elliptic problem. Although the theory for adaptive finite element methods based on residual-type a posteriori error estimator and bisection…

Numerical Analysis · Mathematics 2025-03-24 Jingjing Xiao , Ying Liu , Nianyu Yi

Inferring time-varying graph structures from high-dimensional nodal observations is a fundamental problem arising in neuroscience, finance, climatology, and beyond. Two intrinsic challenges govern this problem: maintaining the…

Machine Learning · Computer Science 2026-05-19 Chuansen Peng , Xiaojing Shen

Transforming into an exact penalty function model with convex compact constraints yields efficient infeasible approaches for optimization problems with orthogonality constraints. For smooth and $\ell_{2,1}$-norm regularized cases, these…

Optimization and Control · Mathematics 2021-10-06 Nachuan Xiao , Xin Liu , Ya-xiang Yuan

This paper develops a high-order selective discontinuous Galerkin (SDG) method for solving elliptic interface problems on interface-unfitted Cartesian meshes. This method applies the discontinuous Galerkin (DG) formulation on interface…

Numerical Analysis · Mathematics 2026-05-20 Fang Liu , Haroun Meghaichi , Xu Zhang

We study the quadratic penalty method (QPM) for smooth nonconvex optimization problems with equality constraints. Assuming the constraint violation satisfies the PL condition near the feasible set, we derive sharper worst-case complexity…

Optimization and Control · Mathematics 2026-01-06 Florentin Goyens , Geovani N. Grapiglia

We establish an interior $C^2$ estimate for $k+1$ convex solutions to Dirichlet problems of $k$-Hessian equations. We also use such estimate to obtain a rigidity theorem for $k+1$ convex entire solutions of $k$-Hessian equations in…

Analysis of PDEs · Mathematics 2020-02-21 MIng Li , Changyu Ren , Zhizhang Wang

In this paper we consider a class of robust multilevel precontioners for the Helmholtz equation with high wave number. The key idea in this work is to use the continuous interior penalty finite element methods (CIP-FEM) studied in…

Numerical Analysis · Mathematics 2013-04-26 Huangxin Chen , Haijun Wu , Xuejun Xu

We propose a new algorithm for sparse estimation of eigenvectors in generalized eigenvalue problems (GEP). The GEP arises in a number of modern data-analytic situations and statistical methods, including principal component analysis (PCA),…

Methodology · Statistics 2020-06-29 Sungkyu Jung , Jeongyoun Ahn , Yongho Jeon

The Huber's criterion is a useful method for robust regression. The adaptive least absolute shrinkage and selection operator (lasso) is a popular technique for simultaneous estimation and variable selection. In the case of small sample size…

Statistics Theory · Mathematics 2012-07-31 Laurent Zwald , Sophie Lambert-Lacroix

Discrete fracture models with reduced-dimensional treatment of conductive and blocking fractures are widely used to simulate fluid flow in fractured porous media. Among these, numerical methods based on interface models are intensively…

Numerical Analysis · Mathematics 2024-05-14 Yong Liu , Ziyao Xu

We provide novel theoretical results regarding local optima of regularized $M$-estimators, allowing for nonconvexity in both loss and penalty functions. Under restricted strong convexity on the loss and suitable regularity conditions on the…

Statistics Theory · Mathematics 2015-01-05 Po-Ling Loh , Martin J. Wainwright

This paper presents a new parameter free partially penalized immersed finite element method and convergence analysis for solving second order elliptic interface problems. A lifting operator is introduced on interface edges to ensure the…

Numerical Analysis · Mathematics 2022-02-23 Haifeng Ji , Feng Wang , Jinru Chen , Zhilin Li

This paper is concerned with solving nonconvex learning problems with folded concave penalty. Despite that their global solutions entail desirable statistical properties, they lack optimization techniques that guarantee global optimality in…

Statistics Theory · Mathematics 2016-03-25 Hongcheng Liu , Tao Yao , Runze Li