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Solving linear systems is a ubiquitous task in science and engineering. Because directly inverting a large-scale linear system can be computationally expensive, iterative algorithms are often used to numerically find the inverse. To…

Numerical Analysis · Mathematics 2021-07-20 Zheyuan Zhu , Andrew B. Klein , Guifang Li , Shuo Pang

By using the Ishikawa iterative algorithm, we approximate the fixed points and the best proximity points of a relatively non expansive mapping. Also, we use the von Neumann sequence to prove the convergence result in a Hilbert space…

Functional Analysis · Mathematics 2020-05-13 V. Pragadeeswarar , R. Gopi , Choonkil Park , Dong Yun Shin

We introduce an abstract algorithm that aims to find the Bregman projection onto a closed convex set. As an application, the asymptotic behaviour of an iterative method for finding a fixed point of a quasi Bregman nonexpansive mapping with…

Functional Analysis · Mathematics 2013-09-26 Heinz H. Bauschke , Jiawei Chen , Xianfu Wang

In structural rigidity, one studies frameworks of bars and joints in Euclidean space. Such a framework is an articulated structure consisting of rigid bars, joined together at joints around which the bars may rotate. In this paper, we will…

Combinatorics · Mathematics 2024-08-28 Joannes Vermant , Klara Stokes

Surrogate models for the rapid inference of nonlinear boundary value problems in mechanics are helpful in a broad range of engineering applications. However, effective surrogate modeling of applications involving the contact of deformable…

Computational Engineering, Finance, and Science · Computer Science 2025-07-21 Vijay K. Dubey , Collin E. Haese , Osman Gültekin , David Dalton , Manuel K. Rausch , Jan N. Fuhg

This paper introduces and demonstrates a computational pipeline for the statistical analysis of shape graph datasets, namely geometric networks embedded in 2D or 3D spaces. Unlike traditional abstract graphs, our purpose is not only to…

Machine Learning · Computer Science 2026-02-19 Murad Hossen , Demetrio Labate , Nicolas Charon

We present an unsupervised data-driven approach for non-rigid shape matching. Shape matching identifies correspondences between two shapes and is a fundamental step in many computer vision and graphics applications. Our approach is designed…

Computer Vision and Pattern Recognition · Computer Science 2023-11-28 Aymen Merrouche , Joao Regateiro , Stefanie Wuhrer , Edmond Boyer

In greedy geometric routing, messages are passed in a network embedded in a metric space according to the greedy strategy of always forwarding messages to nodes that are closer to the destination. We show that greedy geometric routing…

Computational Geometry · Computer Science 2009-10-02 Michael T. Goodrich , Darren Strash

How can one analyze detailed 3D biological objects, such as neurons and botanical trees, that exhibit complex geometrical and topological variation? In this paper, we develop a novel mathematical framework for representing, comparing, and…

Machine Learning · Computer Science 2023-11-28 Guan Wang , Hamid Laga , Anuj Srivastava

The purpose of this paper is to introduce a new Kirk type iterative algorithm called Kirk multistep iteration and to study its convergence. We also prove some theorems related with the stability results for the Kirk-multistep and Kirk-SP…

Functional Analysis · Mathematics 2013-06-11 Faik Gürsoy , Vatan Karakaya , B. E. Rhoades

This paper introduces a set of numerical methods for Riemannian shape analysis of 3D surfaces within the setting of invariant (elastic) second-order Sobolev metrics. More specifically, we address the computation of geodesics and geodesic…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Emmanuel Hartman , Yashil Sukurdeep , Eric Klassen , Nicolas Charon , Martin Bauer

Computing optimal, collision-free trajectories for high-dimensional systems is a challenging problem. Sampling-based planners struggle with the dimensionality, whereas trajectory optimizers may get stuck in local minima due to inherent…

Robotics · Computer Science 2023-05-12 Thomas Cohn , Mark Petersen , Max Simchowitz , Russ Tedrake

Grasp planning and estimation have been a longstanding research problem in robotics, with two main approaches to find graspable poses on the objects: 1) geometric approach, which relies on 3D models of objects and the gripper to estimate…

Robotics · Computer Science 2025-04-11 Xun Tu , Karthik Desingh

Link prediction on graphs is a fundamental problem. Subgraph representation learning approaches (SGRLs), by transforming link prediction to graph classification on the subgraphs around the links, have achieved state-of-the-art performance…

Machine Learning · Computer Science 2024-10-21 Paul Louis , Shweta Ann Jacob , Amirali Salehi-Abari

This paper considers a networked system with a finite number of users and supposes that each user tries to minimize its own private objective function over its own private constraint set. It is assumed that each user's constraint set can be…

Optimization and Control · Mathematics 2015-10-22 Hideaki Iiduka

In the paper, we introduce several accelerate iterative algorithms for solving the multiple-set split common fixed-point problem of quasi-nonexpansive operators in real Hilbert space. Based on primal-dual method, we construct several…

Optimization and Control · Mathematics 2023-06-08 Chenzheng Guo , Jing Zhao

The article presents a new approach to euclidean plane geometry based on projective geometric algebra (PGA). It is designed for anyone with an interest in plane geometry, or who wishes to familiarize themselves with PGA. After a brief…

General Mathematics · Mathematics 2016-11-01 Charles G. Gunn

Strongly regular graphs (SRGs) are highly symmetric combinatorial objects, with connections to many areas of mathematics including finite fields, finite geometries, and number theory. One can construct an SRG via the Cayley Graph of a…

Combinatorics · Mathematics 2024-08-15 Andrew C. Brady

Algorithm unrolling has emerged as a learning-based optimization paradigm that unfolds truncated iterative algorithms in trainable neural-network optimizers. We introduce Stochastic UnRolled Federated learning (SURF), a method that expands…

Machine Learning · Computer Science 2024-02-08 Samar Hadou , Navid NaderiAlizadeh , Alejandro Ribeiro

3D Gaussian Splatting (3DGS) has become a state-of-the-art framework for real-time, high-fidelity novel view synthesis. However, its substantial storage requirements and inherently unstructured representation pose challenges for deployment…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Yuqin Lu , Yang Zhou , Yihua Dai , Guiqing Li , Shengfeng He