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We use convex relaxation techniques to provide a sequence of solutions to the matrix completion problem. Using the nuclear norm as a regularizer, we provide simple and very efficient algorithms for minimizing the reconstruction error…

Machine Learning · Statistics 2009-06-12 Rahul Mazumder , Trevor Hastie , Rob Tibshirani

The image deblurring problem consists of reconstructing images from blur and noise contaminated available data. In this AMS Notices article, we provide an overview of some well known numerical linear algebra techniques that are use for…

Numerical Analysis · Mathematics 2022-01-25 David Austin , Malena I. Español , Mirjeta Pasha

This paper presents an iterative method suitable for inverting semilinear problems which are important kernels in many numerical applications. The primary idea is to employ a parametrization that is able to reduce semilinear problems into…

Numerical Analysis · Mathematics 2019-08-02 Prosper Torsu

There are many practical applications that require simplification of polylines. Some of the goals are to reduce the amount of information necessary to store, improve processing time, or simplify editing. The simplification is usually done…

Computational Geometry · Computer Science 2018-12-12 Alexander Gribov

Snow removal aims to locate snow areas and recover clean images without repairing traces. Unlike the regularity and semitransparency of rain, snow with various patterns and degradations seriously occludes the background. As a result, the…

Computer Vision and Pattern Recognition · Computer Science 2023-04-07 Junhong Lin , Nanfeng Jiang , Zhentao Zhang , Weiling Chen , Tiesong Zhao

This paper introduces a novel algorithm for Mixed-Integer Nonlinear Programming (MINLP) problems with multilinear interpolations of look-up tables. These problems arise when objective or constraints contain black-box functions only known at…

We present a scalable combinatorial algorithm for globally optimizing over the space of geometrically consistent mappings between 3D shapes. We use the mathematically elegant formalism proposed by Windheuser et al. (ICCV 2011) where 3D…

Computer Vision and Pattern Recognition · Computer Science 2022-04-28 Paul Roetzer , Paul Swoboda , Daniel Cremers , Florian Bernard

We present a new algorithm for computing a truncated Markov basis of a lattice. In general, this new algorithm is faster than existing methods. We then extend this new algorithm so that it solves the linear integer feasibility problem with…

Optimization and Control · Mathematics 2007-05-23 Peter N. Malkin

This paper describes an efficient approach to constructing a resultant polyline with a minimum number of segments and arcs. While fitting an arc can be done with complexity O(1) (see [1] and [2]), the main complexity is in checking that the…

Computational Geometry · Computer Science 2017-04-12 Alexander Gribov

In this paper we are concerned with three lattice problems: the lattice packing problem, the lattice covering problem and the lattice packing-covering problem. One way to find optimal lattices for these problems is to enumerate all finitely…

Metric Geometry · Mathematics 2008-09-26 Achill Schuermann , Frank Vallentin

The cutting plane approach to optimal matchings has been discussed by several authors over the past decades (e.g., Padberg and Rao '82, Grotschel and Holland '85, Lovasz and Plummer '86, Trick '87, Fischetti and Lodi '07) and its…

Data Structures and Algorithms · Computer Science 2014-01-24 Karthekeyan Chandrasekaran , Laszlo A. Vegh , Santosh Vempala

By some new recursive algorithms, in this paper, we will give some improvements on Waring's problem.

Combinatorics · Mathematics 2020-02-11 An-Ping Li

Sketch techniques have been extensively studied in recent years and are especially well-suited to data streaming scenarios, where the sketch summary is updated quickly and compactly. However, it is challenging to recover the current state…

Machine Learning · Computer Science 2026-03-17 Xinyu Yuan , Yan Qiao , Zonghui Wang , Wenzhi Chen

In this paper, we introduce the solver ConvexFlows for the convex flow problem first defined in the authors' previous work. In this problem, we aim to optimize a concave utility function depending on the flows over a graph. However, unlike…

Optimization and Control · Mathematics 2024-08-21 Theo Diamandis , Guillermo Angeris

Most efficient linear solvers use composable algorithmic components, with the most common model being the combination of a Krylov accelerator and one or more preconditioners. A similar set of concepts may be used for nonlinear algebraic…

Numerical Analysis · Mathematics 2016-07-15 Peter R. Brune , Matthew G. Knepley , Barry F. Smith , Xuemin Tu

We study several variations of line segment covering problem with axis-parallel unit squares in $I\!\!R^2$. A set $S$ of $n$ line segments is given. The objective is to find the minimum number of axis-parallel unit squares which cover at…

Computational Geometry · Computer Science 2016-09-28 Ankush Acharyya , Subhas C. Nandy , Supantha Pandit , Sasanka Roy

A popular approach to sentence compression is to formulate the task as a constrained optimization problem and solve it with integer linear programming (ILP) tools. Unfortunately, dependence on ILP may make the compressor prohibitively slow,…

Computation and Language · Computer Science 2015-10-29 Katja Filippova , Enrique Alfonseca

Trimming is a core technique in geometric modeling. Unfortunately, the resulting objects do not take the requirements of numerical simulations into account and yield various problems. This paper outlines principal issues of trimmed models…

Graphics · Computer Science 2019-02-05 Benjamin Marussig

Recent progress in Zauner's conjecture has leveraged deep conjectures in algebraic number theory to promote numerical line packings to exact and verifiable solutions to the line packing problem. We introduce a numerical-to-exact technique…

Metric Geometry · Mathematics 2019-05-02 Dustin G. Mixon , Hans Parshall

We consider a setting in which it is desired to find an optimal complex vector $\mathbf{x}\in\mathbb{C}^N$ that satisfies $\mathcal{A}(\mathbf{x}) \approx \mathbf{b}$ in a least-squares sense, where $\mathbf{b} \in \mathbb{C}^M$ is a data…

Numerical Analysis · Mathematics 2020-07-21 Tae Hyung Kim , Justin P. Haldar
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