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In high-contrast composites, the electric (or stress) field may exhibit significant amplification in the narrow region between inclusions. The behavior of the solution depends on the distance $\epsilon$ between the inclusions, which tends…

Analysis of PDEs · Mathematics 2026-04-28 Linjie Ma

We propose a multiscale method for mixed-dimensional elliptic problems with highly heterogeneous coefficients arising, for example, in the modeling of fractured porous media. The method is based on the Localized Orthogonal Decomposition…

Numerical Analysis · Mathematics 2026-03-23 Moritz Hauck , Axel Målqvist , Malin Mosquera

High-dimensional statistical inference deals with models in which the the number of parameters p is comparable to or larger than the sample size n. Since it is usually impossible to obtain consistent procedures unless $p/n\rightarrow0$, a…

Statistics Theory · Mathematics 2013-03-13 Sahand N. Negahban , Pradeep Ravikumar , Martin J. Wainwright , Bin Yu

We study robust convex quadratic programs where the uncertain problem parameters can contain both continuous and integer components. Under the natural boundedness assumption on the uncertainty set, we show that the generic problems are…

Optimization and Control · Mathematics 2018-12-19 Areesh Mittal , Can Gokalp , Grani A. Hanasusanto

In this paper, we propose a unified algorithmic framework for solving many known variants of \mds. Our algorithm is a simple iterative scheme with guaranteed convergence, and is \emph{modular}; by changing the internals of a single…

Machine Learning · Computer Science 2010-03-31 Arvind Agarwal , Jeff M. Phillips , Suresh Venkatasubramanian

This paper is devoted to the construction of order reduced method of fourth order problems. A framework is presented such that a problem on a high-regularity space can be deduced in a constructive way to an equivalent problem on three…

Numerical Analysis · Mathematics 2016-11-02 Shuo Zhang

The Multiscale Hierarchical Decomposition Method (MHDM) was introduced as an iterative method for total variation regularization, with the aim of recovering details at various scales from images corrupted by additive or multiplicative…

Numerical Analysis · Mathematics 2023-09-28 Stefan Kindermann , Elena Resmerita , Tobias Wolf

This paper introduces a novel variational Bayesian method that integrates Tucker decomposition for efficient high-dimensional inverse problem solving. The method reduces computational complexity by transforming variational inference from a…

Machine Learning · Computer Science 2026-03-18 Qing-Mei Yang , Da-Qing Zhang

We study a nonlinear decomposition of a positive definite matrix into two components: the inverse of another positive definite matrix and a symmetric matrix constrained to lie in a prescribed linear subspace. Equivalently, the inverse…

Optimization and Control · Mathematics 2026-01-27 Yan Dolinsky , Or Zuk

A preasymptotic error analysis of the finite element method (FEM) and some continuous interior penalty finite element method (CIP-FEM) for Helmholtz equation in two and three dimensions is proposed. $H^1$- and $L^2$- error estimates with…

Numerical Analysis · Mathematics 2014-01-20 Yu Du , Haijun Wu

The (matricial) solution set of a Linear Matrix Inequality (LMI) is a convex basic non-commutative semi-algebraic set. The main theorem of this paper is a converse, a result which has implications for both semidefinite programming and…

Functional Analysis · Mathematics 2011-08-31 J. William Helton , Scott McCullough

We examine the use of a two-level deflation preconditioner combined with GMRES to locally solve the subdomain systems arising from applying domain decomposition methods to Helmholtz problems. Our results show that the direct solution method…

Numerical Analysis · Mathematics 2023-05-03 Niall Bootland , Vandana Dwarka , Pierre Jolivet , Victorita Dolean , Cornelis Vuik

The high-frequency Helmholtz equation on the entire space is truncated into a bounded domain using the perfectly matched layer (PML) technique and subsequently, discretized by the higher-order finite element method (FEM) and the continuous…

Numerical Analysis · Mathematics 2023-12-06 Yonglin Li , Haijun Wu

A method for the analytical evaluation of layer potentials arising in the collocation boundary element method for the Laplace and Helmholtz equation is developed for piecewise flat boundary elements with polynomial shape functions. The…

Numerical Analysis · Mathematics 2023-02-07 Shoken Kaneko , Nail A. Gumerov , Ramani Duraiswami

In this paper, a least-squares finite element method for scalar nonlinear hyperbolic balance laws is proposed and studied. The approach is based on a formulation that utilizes an appropriate Helmholtz decomposition of the flux vector and is…

Numerical Analysis · Mathematics 2020-10-06 Delyan Z. Kalchev , Thomas A. Manteuffel

The impressive capabilities of large foundation models come at a cost of substantial computing resources to serve them. Compressing these pre-trained models is of practical interest as it can democratize deploying them to the machine…

Machine Learning · Statistics 2025-02-04 Mehdi Makni , Kayhan Behdin , Zheng Xu , Natalia Ponomareva , Rahul Mazumder

We focus on two central themes in this dissertation. The first one is on decomposing polytopes and polynomials in ways that allow us to perform nonlinear optimization. We start off by explaining important results on decomposing a polytope…

Combinatorics · Mathematics 2016-05-18 Brandon Dutra

We consider the offset-deconstruction problem: Given a polygonal shape Q with n vertices, can it be expressed, up to a tolerance \eps in Hausdorff distance, as the Minkowski sum of another polygonal shape P with a disk of fixed radius? If…

Computational Geometry · Computer Science 2011-09-13 Eric Berberich , Dan Halperin , Michael Kerber , Roza Pogalnikova

We consider the demixing problem of two (or more) high-dimensional vectors from nonlinear observations when the number of such observations is far less than the ambient dimension of the underlying vectors. Specifically, we demonstrate an…

Machine Learning · Statistics 2017-01-25 Mohammadreza Soltani , Chinmay Hegde

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
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