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We apply an unfitted HDG discretization to a model problem in shape optimization. The method proposed uses a fixed, shape regular, non-geometry conforming mesh and a high order transfer technique to deal with the curved boundaries arising…

Numerical Analysis · Mathematics 2025-09-30 Esteban Henríquez , Tonatiuh Sánchez-Vizuet , Manuel Solano

Converting a parametric curve into the implicit form, which is called implicitization, has always been a popular but challenging problem in geometric modeling and related applications. However, the existing methods mostly suffer from the…

Graphics · Computer Science 2023-02-24 Minghao Guo , Yan Gao , Zheng Pan

We consider the problem of approximating a two-dimensional shape contour (or curve segment) using discrete assembly systems, which allow to build geometric structures based on limited sets of node and edge types subject to edge length and…

Computational Geometry · Computer Science 2021-02-03 Andreas M. Tillmann , Leif Kobbelt

We consider the inverse obstacle scattering problem of determining both the shape and the "equivalent impedance" from far field measurements at a fixed frequency. In this work, the surface impedance is represented by a second order surface…

Numerical Analysis · Mathematics 2013-07-24 Laurent Bourgeois , Nicolas Chaulet , Houssem Haddar

In this paper, we derive new shape descriptors based on a directional characterization. The main idea is to study the behavior of the shape neighborhood under family of transformations. We obtain a description invariant with respect to…

Computer Vision and Pattern Recognition · Computer Science 2013-02-26 Xavier Descombes , Serguei Komech

The rapidly evolving field of engineering design of functional surfaces necessitates sophisticated tools to manage the inherent complexity of high-dimensional design spaces. This survey paper offers a scoping review, i.e., a literature…

Optimization and Control · Mathematics 2025-04-09 Andrea Serani , Matteo Diez

Inspired by regularization techniques in statistics and machine learning, we study complementary composite minimization in the stochastic setting. This problem corresponds to the minimization of the sum of a (weakly) smooth function endowed…

Machine Learning · Computer Science 2024-01-24 Alexandre d'Aspremont , Cristóbal Guzmán , Clément Lezane

We study implicit regularization when optimizing an underdetermined quadratic objective over a matrix $X$ with gradient descent on a factorization of $X$. We conjecture and provide empirical and theoretical evidence that with small enough…

Machine Learning · Statistics 2017-05-26 Suriya Gunasekar , Blake Woodworth , Srinadh Bhojanapalli , Behnam Neyshabur , Nathan Srebro

Algorithms for continuous optimization problems have a rich history of design and innovation over the past several decades, in which mathematical analysis of their convergence and complexity properties plays a central role. Besides their…

Optimization and Control · Mathematics 2025-12-03 Stephen J. Wright

Implicit regularization refers to the tendency of local search algorithms to converge to low-dimensional solutions, even when such structures are not explicitly enforced. Despite its ubiquity, the mechanism underlying this behavior remains…

Machine Learning · Computer Science 2025-12-10 Jianhao Ma , Geyu Liang , Salar Fattahi

Structural optimization is a popular method for designing objects such as bridge trusses, airplane wings, and optical devices. Unfortunately, the quality of solutions depends heavily on how the problem is parameterized. In this paper, we…

Machine Learning · Computer Science 2019-09-17 Stephan Hoyer , Jascha Sohl-Dickstein , Sam Greydanus

We propose a discretization of classical confocal coordinates. It is based on a novel characterization thereof as factorizable orthogonal coordinate systems. Our geometric discretization leads to factorizable discrete nets with a novel…

Differential Geometry · Mathematics 2019-11-11 Alexander I. Bobenko , Wolfgang K. Schief , Yuri B. Suris , Jan Techter

Recent advances in implicit neural representations show great promise when it comes to generating numerical solutions to partial differential equations. Compared to conventional alternatives, such representations employ parameterized neural…

Machine Learning · Computer Science 2021-11-29 Jonas Zehnder , Yue Li , Stelian Coros , Bernhard Thomaszewski

The rules in a shape grammar apply in terms of embedding to take advantage of the parts that emerge visually in the appearance of shapes. While the shapes are kept unanalyzed as a computation moves forward, part-structures for shapes can be…

Formal Languages and Automata Theory · Computer Science 2022-03-15 Alexandros Haridis , George Stiny

We present a general approach for the treatment of parameterized geometries in projection-based model order reduction. During the offline stage, given (i) a family of parameterized domains $\{ \Omega_{\mu}: \mu \in \mathcal{P} \} \subset…

Numerical Analysis · Mathematics 2021-07-07 Tommaso Taddei , Lei Zhang

We discuss a general technique that can be used to form a differentiable bound on the optima of non-differentiable or discrete objective functions. We form a unified description of these methods and consider under which circumstances the…

Machine Learning · Statistics 2012-12-21 Joe Staines , David Barber

Manifold optimization is ubiquitous in computational and applied mathematics, statistics, engineering, machine learning, physics, chemistry and etc. One of the main challenges usually is the non-convexity of the manifold constraints. By…

Optimization and Control · Mathematics 2019-06-14 Jiang Hu , Xin Liu , Zaiwen Wen , Yaxiang Yuan

In a previous paper, we provided some update in the treatment of the finiteness theorem for rational maps of finite degree from a fixed variety to varieties of general type. In the present paper we present another improvement, introducing…

Algebraic Geometry · Mathematics 2012-03-13 Lucio Guerra , Gian Pietro Pirola

Ceramic is a material frequently used in industry because of its favorable properties. Common approaches in shape optimization for ceramic structures aim to minimize the tensile stress acting on the component, as it is the main driver for…

Optimization and Control · Mathematics 2017-05-17 Matthias Bolten , Hanno Gottschalk , Camilla Hahn , Mohamed Saadi

The modelling of discrete regulatory networks combines a graph specifying the pairwise influences between the variables of the system, and a parametrisation from which can be derived a discrete transition system. Given the influence graph…

Discrete Mathematics · Computer Science 2018-03-19 Juraj Kolčák , David Šafránek , Stefan Haar , Loïc Paulevé
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