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Sketched gradient algorithms have been recently introduced for efficiently solving the large-scale constrained Least-squares regressions. In this paper we provide novel convergence analysis for the basic method {\it Gradient Projection…

Optimization and Control · Mathematics 2017-06-05 Junqi Tang , Mohammad Golbabaee , Mike Davies

The paper describes a novel real-time algorithm for finding 3D geometric primitives (cylinders, cones and spheres) from 3D range data. In its core, it performs a fast model fitting with a model update in constant time (O(1)) for each new…

Computer Vision and Pattern Recognition · Computer Science 2016-03-15 Kristiyan Georgiev , Motaz Al-Hami , Rolf Lakaemper

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

For the numerical solution of shape optimization problems, particularly those constrained by partial differential equations (PDEs), the quality of the underlying mesh is of utmost importance. Particularly when investigating complex…

Optimization and Control · Mathematics 2025-10-14 Sebastian Blauth , Christian Leithäuser

Purpose: Field monitoring measures field perturbations, which can be accounted for during image reconstructions. In certain field monitoring environments, significant phase deviations can arise far from isocenter due to the finite extent of…

Medical Physics · Physics 2023-01-25 Paul I. Dubovan , Kyle M. Gilbert , Corey A. Baron

State-of-the-art object pose estimation methods are prone to generating geometrically infeasible pose hypotheses. This problem is prevalent in dexterous manipulation, where estimated poses often intersect with the robotic hand or are not…

Robotics · Computer Science 2026-03-24 Anil Zeybek , Rhys Newbury , Snehal Dikhale , Nawid Jamali , Soshi Iba , Akansel Cosgun

With the popularity of drone technologies, aerial photography has become prevalent in many daily scenarios such as environment monitoring, structure inspection, law enforcement etc. A central challenge in this domain is the efficient…

Robotics · Computer Science 2025-12-30 Si Wei Feng

In this paper, we provide a new scheme for approximating the weakly efficient solution set for a class of vector optimization problems with rational objectives over a feasible set defined by finitely many polynomial inequalities. More…

Optimization and Control · Mathematics 2022-05-26 Feng Guo , Liguo Jiao

In multi-objective optimization, computing the entire non-dominated set (also known as the Pareto front or the Pareto frontier) is often intractable. However, for any multiplicative factor greater than one, an approximation set can be…

Optimization and Control · Mathematics 2026-04-30 Levin Nemesch , Stefan Ruzika , Clemens Thielen , Alina Wittmann

Real-time object pose estimation is necessary for many robot manipulation algorithms. However, state-of-the-art methods for object pose estimation are trained for a specific set of objects; these methods thus need to be retrained to…

Computer Vision and Pattern Recognition · Computer Science 2022-04-28 Qiao Gu , Brian Okorn , David Held

The Fast Proximal Gradient Method (FPGM) and the Monotone FPGM (MFPGM) for minimization of nonsmooth convex functions are introduced and applied to tomographic image reconstruction. Convergence properties of the sequence of objective…

Optimization and Control · Mathematics 2020-08-25 Elias S. Helou , Marcelo V. W. Zibetti , Gabor T. Herman

We consider the projected gradient algorithm for the nonconvex best subset selection problem that minimizes a given empirical loss function under an $\ell_0$-norm constraint. Through decomposing the feasible set of the given sparsity…

Optimization and Control · Mathematics 2026-02-13 Jan Harold Alcantara , Ching-pei Lee

We consider the problem of minimizing the sum of two convex functions: one is differentiable and relatively smooth with respect to a reference convex function, and the other can be nondifferentiable but simple to optimize. We investigate a…

Optimization and Control · Mathematics 2021-06-01 Filip Hanzely , Peter Richtarik , Lin Xiao

Image Phase Alignment Super-sampling (ImPASS) is a computational method for combining displaced low-resolution images into a single high-resolution image. The general steps include measuring the relative displacements, up-sampling, aligning…

Optics · Physics 2026-01-09 James N. Caron

In this paper, we introduce and study the Parallel Polyhedral Projection Method (3PM) and the Approximate Parallel Polyhedral Projection Method (A3PM) for finding a point in the intersection of finitely many closed convex sets. Each…

Optimization and Control · Mathematics 2025-06-27 Pablo Barros , Roger Behling , Vincent Guigues

In many applications of tomography, the acquired projections are either limited in number or contain a significant amount of noise. In these cases, standard reconstruction methods tend to produce artifacts that can make further analysis…

Numerical Analysis · Mathematics 2016-04-11 D. M. Pelt , K. J. Batenburg

This thesis presents important insights and concepts related to the topic of the extraction of geometric primitives from the edge contours of digital images. Three specific problems related to this topic have been studied, viz., polygonal…

Computer Vision and Pattern Recognition · Computer Science 2013-05-17 Dilip K. Prasad

Spectral polynomial approximation of smooth functions allows real-time manipulation of and computation with them, as in the Chebfun system. Extension of the technique to two-dimensional and three-dimensional functions on hyperrectangles has…

Numerical Analysis · Mathematics 2019-01-21 Kevin W. Aiton , Tobin A. Driscoll

We discuss Coarse Grid Projection (CGP) methodology as a guide for partial mesh refinement of incompressible flow computations for the first time. Based on it, if for a given spatial resolution the numerical simulation diverges or the…

Computational Physics · Physics 2018-03-29 Ali Kashefi

In this paper, we propose a new algorithm to speed-up the convergence of accelerated proximal gradient (APG) methods. In order to minimize a convex function $f(\mathbf{x})$, our algorithm introduces a simple line search step after each…

Machine Learning · Statistics 2014-06-19 Ziming Zhang , Venkatesh Saligrama