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We study some methods of subgradient projections for solving a convex feasibility problem with general (not necessarily hyperplanes or half-spaces) convex sets in the inconsistent case and propose a strategy that controls the relaxation…

Optimization and Control · Mathematics 2010-09-21 Dan Butnariu , Yair Censor , Pini Gurfil , Ethan Hadar

By exploiting double-penalty terms for the primal subproblem, we develop a novel relaxed augmented Lagrangian method for solving a family of convex optimization problems subject to equality or inequality constraints. The method is then…

Numerical Analysis · Mathematics 2025-06-16 Jianchao Bai , Linyuan Jia , Zheng Peng

This paper presents a new representation of curve dynamics, with applications to vortex filaments in fluid dynamics. Instead of representing these filaments with explicit curve geometry and Lagrangian equations of motion, we represent…

Graphics · Computer Science 2022-09-29 Sadashige Ishida , Chris Wojtan , Albert Chern

Gradient descent can be surprisingly good at optimizing deep neural networks without overfitting and without explicit regularization. We find that the discrete steps of gradient descent implicitly regularize models by penalizing gradient…

Machine Learning · Computer Science 2022-07-20 David G. T. Barrett , Benoit Dherin

Including derivative information in the modelling of moving interfaces has been proposed as one method to increase the accuracy of numerical schemes with minimal additional cost. Here a new level set reinitialization technique using the…

Numerical Analysis · Mathematics 2011-11-30 David Salac

This paper introduces a sharp interface method to simulate fluid-structure interaction (FSI) involving rigid bodies immersed in viscous incompressible fluids. The capabilities of this methodology are demonstrated for a range of benchmark…

Gradient-based iterative optimization methods are the workhorse of modern machine learning. They crucially rely on careful tuning of parameters like learning rate and momentum. However, one typically sets them using heuristic approaches…

Machine Learning · Computer Science 2025-12-05 Dravyansh Sharma

Recent advancements in photo-realistic novel view synthesis have been significantly driven by Gaussian Splatting (3DGS). Nevertheless, the explicit nature of 3DGS data entails considerable storage requirements, highlighting a pressing need…

Computer Vision and Pattern Recognition · Computer Science 2024-11-12 Minye Wu , Tinne Tuytelaars

We developed a sharp interface level-set approach for two-phase immiscible flow with moving contact lines. The Cox-Voinov model is used to describe the moving contact line. A piecewise linear interface method is used to construct the signed…

Fluid Dynamics · Physics 2017-10-26 Moataz O. Abu-Al-Saud , Cyprien Soulaine , Amir Riaz , Hamdi A. Tchelepi

Diffuse interface methods have recently been introduced for the task of semi-supervised learning. The underlying model is well-known in materials science but was extended to graphs using a Ginzburg--Landau functional and the graph…

Machine Learning · Statistics 2016-11-21 Jessica Bosch , Steffen Klamt , Martin Stoll

A new class of semi-implicit numerical schemes for linear advection equation on Cartesian grids is derived that is inspired by so-called $\kappa$-schemes used with fully explicit discretizations for this type of problems. Opposite to fully…

Numerical Analysis · Mathematics 2016-11-15 Peter Frolkovič , Karol Mikula

An explicit high order semi-Lagrangian method is developed for solving Lagrangian transport equations in Eulerian-Lagrangian formulations. To ensure a semi-Lagrangian approximation that is consistent with an explicit Eulerian, discontinuous…

Numerical Analysis · Mathematics 2019-10-16 Hareshram Natarajan , Gustaaf B. Jacobs

As one of the most popular interface-capturing methods, the level-set method is inherently non-conservative, and its evolution usually leads to unphysical mass gain/loss. In this paper, a novel conservative level set method is developed for…

Computational Physics · Physics 2022-02-22 Tian Long , Jinsheng Cai , Shucheng Pan

With the vigorous development of artificial intelligence technology, various engineering technology applications have been implemented one after another. The gradient descent method plays an important role in solving various optimization…

Machine Learning · Computer Science 2021-04-27 Jinhuan Duan , Xianxian Li , Shiqi Gao , Jinyan Wang , Zili Zhong

Feature selection is an important and active research area in statistics and machine learning. The Elastic Net is often used to perform selection when the features present non-negligible collinearity or practitioners wish to incorporate…

Machine Learning · Statistics 2020-06-09 Tobia Boschi , Matthew Reimherr , Francesca Chiaromonte

This paper is devoted to first-order algorithms for smooth convex optimization with inexact gradients. Unlike the majority of the literature on this topic, we consider the setting of relative rather than absolute inexactness. More…

Optimization and Control · Mathematics 2023-10-03 Nikita Kornilov , Eduard Gorbunov , Mohammad Alkousa , Fedor Stonyakin , Pavel Dvurechensky , Alexander Gasnikov

The performance of traditional graph Laplacian methods for semi-supervised learning degrades substantially as the ratio of labeled to unlabeled data decreases, due to a degeneracy in the graph Laplacian. Several approaches have been…

Analysis of PDEs · Mathematics 2019-04-03 Jeff Calder , Dejan Slepcev

This work focuses on a class of elliptic boundary value problems with diffusive, advective and reactive terms, motivated by the study of three-dimensional heterogeneous physical systems composed of two or more media separated by a selective…

Numerical Analysis · Mathematics 2018-04-20 Riccardo Sacco , Aurelio Giancarlo Mauri , Giovanna Guidoboni

In this paper, we propose a novel gradient recovery method for elliptic interface problem using body-fitted mesh in two dimension. Due to the lack of regularity of solution at interface, standard gradient recovery methods fail to give…

Numerical Analysis · Mathematics 2016-07-21 Hailong Guo , Xu Yang

Attaining reliable profile gradients is of utmost relevance for many physical systems. In most situations, the estimation of gradient can be inaccurate due to noise. It is common practice to first estimate the underlying system and then…

Data Analysis, Statistics and Probability · Physics 2021-05-31 Kushani De Silva , Carlo Cafaro , Adom Giffin
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