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This paper presents some applications using recently developed algorithms for smooth-continuous data reconstruction based on the digital-discrete method. The classical discrete method for data reconstruction is based on domain decomposition…

Numerical Analysis · Mathematics 2010-03-23 Li Chen

Constrained second-order convex optimization algorithms are the method of choice when a high accuracy solution to a problem is needed, due to their local quadratic convergence. These algorithms require the solution of a constrained…

Optimization and Control · Mathematics 2025-06-13 Alejandro Carderera , Sebastian Pokutta

Coordinate descent methods have considerable impact in global optimization because global (or, at least, almost global) minimization is affordable for low-dimensional problems. Coordinate descent methods with high-order regularized models…

Optimization and Control · Mathematics 2023-04-28 V. S. Amaral , R. Andreani , E. G. Birgin , D. S. Marcondes , J. M. Martínez

We consider in this paper a class of composite optimization problems whose objective function is given by the summation of a general smooth and nonsmooth component, together with a relatively simple nonsmooth term. We present a new class of…

Optimization and Control · Mathematics 2015-10-27 Guanghui Lan

We present the `Basic S*' algorithm for computing shortest path through a metric simplicial complex. In particular, given a metric graph, $G$, which is constructed as a discrete representation of an underlying configuration space (a larger…

Discrete Mathematics · Computer Science 2016-08-09 Subhrajit Bhattacharya

We propose a novel tree-like curvilinear structure reconstruction algorithm based on supervised learning and graph theory. In this work we analyze image patches to obtain the local major orientations and the rankings that correspond to the…

Computer Vision and Pattern Recognition · Computer Science 2016-12-09 Seong-Gyun Jeong , Yuliya Tarabalka , Nicolas Nisse , Josiane Zerubia

We consider in this paper a class of single-ratio fractional minimization problems, in which the numerator part of the objective is the sum of a nonsmooth nonconvex function and a smooth nonconvex function while the denominator part is a…

Optimization and Control · Mathematics 2020-12-23 Na Zhang , Qia Li

In the planted partition problem, the $n$ vertices of a random graph are partitioned into $k$ "clusters," and edges between vertices in the same cluster and different clusters are included with constant probability $p$ and $q$, respectively…

Data Structures and Algorithms · Computer Science 2017-08-24 Sam Cole

In computer graphics, smooth data reconstruction on 2D or 3D manifolds usually refers to subdivision problems. Such a method is only valid based on dense sample points. The manifold usually needs to be triangulated into meshes (or patches)…

Numerical Analysis · Mathematics 2011-05-30 Li Chen , Feng Luo

In this work, we develop a fully implicit Hybrid High-Order algorithm for the Cahn-Hilliard problem in mixed form. The space discretization hinges on local reconstruction operators from hybrid polynomial unknowns at elements and faces. The…

Numerical Analysis · Mathematics 2016-07-01 Florent Chave , Daniele A. Di Pietro , Fabien Marche , Franck Pigeonneau

In this paper, we study an unconventional but practically meaningful reversibility problem of commonly used image filters. We broadly define filters as operations to smooth images or to produce layers via global or local algorithms. And we…

Computer Vision and Pattern Recognition · Computer Science 2017-04-14 Xin Tao , Chao Zhou , Xiaoyong Shen , Jue Wang , Jiaya Jia

We consider the problem of subspace clustering: given points that lie on or near the union of many low-dimensional linear subspaces, recover the subspaces. To this end, one first identifies sets of points close to the same subspace and uses…

Machine Learning · Statistics 2014-11-03 Dohyung Park , Constantine Caramanis , Sujay Sanghavi

In this work, we study the perception problem for sampled surfaces (possibly with boundary) using tools from computational topology, specifically, how to identify their underlying topology starting from point-cloud samples in space, such as…

Computational Geometry · Computer Science 2024-10-17 Franco Coltraro , Jaume Amorós , Maria Alberich-Carramiñana , Carme Torras

There are many space subdivision and space partitioning techniques used in many algorithms to speed up computations. They mostly rely on orthogonal space subdivision, resp. using hierarchical data structures, e.g. BSP trees, quadtrees,…

Graphics · Computer Science 2022-08-09 Vaclav Skala

Obtaining high quality particle distribution representing clean geometry in pre-processing is essential for the simulation accuracy of the particle-based methods. In this paper, several level-set based techniques for cleaning up `dirty'…

Computational Engineering, Finance, and Science · Computer Science 2023-05-01 Yongchuan Yu , Yujie Zhu , Chi Zhang , Oskar J. Haidn , Xiangyu Hu

We propose a new method for the reconstruction of simplicial complexes (combining points, edges and triangles) from 3D point clouds from Mobile Laser Scanning (MLS). Our main goal is to produce a reconstruction of a scene that is adapted to…

Graphics · Computer Science 2018-04-10 Stephane Guinard , Bruno Vallet

Topological features play an essential role in ensuring geometric plausibility and structural consistency in image analysis tasks such as segmentation and skeletonization. However, integrating topology-preserving learning based on simple…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Wenxiao Li , Faqiang Wang , Yuping Duan , Li Cui , Liqiang Zhang , Jun Liu

We present an efficient, trivially parallelizable algorithm to compute offset surfaces of shapes discretized using a dexel data structure. Our algorithm is based on a two-stage sweeping procedure that is simple to implement and efficient,…

Graphics · Computer Science 2019-04-10 Zhen Chen , Daniele Panozzo , Jeremie Dumas

In this paper, we consider the planted partition model, in which $n = ks$ vertices of a random graph are partitioned into $k$ "clusters," each of size $s$. Edges between vertices in the same cluster and different clusters are included with…

Data Structures and Algorithms · Computer Science 2017-08-28 Sam Cole , Shmuel Friedland , Lev Reyzin

Recent advances (Sherman, 2017; Sidford and Tian, 2018; Cohen et al., 2021) have overcome the fundamental barrier of dimension dependence in the iteration complexity of solving $\ell_\infty$ regression with first-order methods. Yet it…

Optimization and Control · Mathematics 2025-06-18 Cedar Site Bai , Brian Bullins
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