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We consider the variable selection problem of generalized linear models (GLMs). Stability selection (SS) is a promising method proposed for solving this problem. Although SS provides practical variable selection criteria, it is…

Machine Learning · Statistics 2025-08-06 Takashi Takahashi , Yoshiyuki Kabashima

The gas-kinetic scheme(GKS) is a promising computational fluid dynamics (CFD) method for solving the Navier-Stokes equations. It is based on the analytical solution of the BGK equation, which enables accurate and robust simulations. While…

Fluid Dynamics · Physics 2025-08-12 Yue Zhang , Xing Ji , Kun Xu

We investigate the accuracy and robustness of one of the most common methods used in glaciology for the discretization of the $\mathfrak{p}$-Stokes equations: equal order finite elements with Galerkin Least-Squares (GLS) stabilization.…

Computational Physics · Physics 2019-07-30 Christian Helanow , Josefin Ahlkrona

When training neural networks with full-batch gradient descent (GD) and step size $\eta$, the largest eigenvalue of the Hessian -- the sharpness $S(\boldsymbol{\theta})$ -- rises to $2/\eta$ and hovers there, a phenomenon termed the Edge of…

Machine Learning · Computer Science 2026-04-24 Fangshuo Liao , Afroditi Kolomvaki , Anastasios Kyrillidis

The general synthetic iteration scheme (GSIS) is extended to find the steady-state solution of nonlinear gas kinetic equation, removing the long-standing problems of slow convergence and requirement of ultra-fine grids in near-continuum…

Computational Physics · Physics 2021-02-24 Lianhua Zhu , Xingcai Pi , Wei Su , Zhi-Hui Li , Yonghao Zhang , Lei Wu

The recently-developed general synthetic iterative scheme (GSIS) is efficient in simulating multiscale rarefied gas flows due to the coupling of mesoscopic kinetic equation and macroscopic synthetic equation: for linearized Poiseuille flow…

Fluid Dynamics · Physics 2023-11-07 Wei Liu , Yanbing Zhang , Jianan Zeng , Lei Wu

The efficient solution of large sparse saddle point systems is very important in computational fluid mechanics. The discontinuous Galerkin finite element methods have become increasingly popular for incompressible flow problems but their…

Mathematical Software · Computer Science 2021-01-18 Denis Demidov , Lin Mu , Bin Wang

In this paper, we present a novel general framework grounded in the factor graph theory to solve kinematic and dynamic problems for multi-body systems. Although the motion of multi-body systems is considered to be a well-studied problem and…

Robotics · Computer Science 2021-07-27 José-Luis Blanco-Claraco , Antonio Leanza , Giulio Reina

The Gaussian-filtered Navier-Stokes equations are examined theoretically and a generalized theory of their numerical stability is proposed. Using the exact expansion series of subfilter-scale stresses or integration by parts, the terms…

Fluid Dynamics · Physics 2007-05-23 Masato Ida , Nobuyuki Oshima

Optimization algorithms are unlikely to converge to strict saddle points. Proofs to that effect rely on the Center-Stable Manifold Theorem (CSMT), casting algorithms as dynamical systems: $x_{k+1} = g_k(x_k)$. In its standard form, the CSMT…

Optimization and Control · Mathematics 2026-05-05 Andreea-Alexandra Muşat , Nicolas Boumal

A method for enhancing the stability and robustness of explicit schemes in computational fluid dynamics is presented. The method is based in reformulating explicit schemes in matrix form, which cane modified gradually into semi or…

Mathematical Physics · Physics 2009-11-10 A. A. Hujeirat

In this paper, we are interested in investigating notions of stability for generalized linear differential equations (GLDEs). Initially, we propose and revisit several definitions of stability and provide a complete characterisation of them…

Classical Analysis and ODEs · Mathematics 2023-02-16 Claudio A. Gallegos , Gonzalo Robledo

The dynamical stability of the iterates during training plays a key role in determining the minima obtained by optimization algorithms. For example, stable solutions of gradient descent (GD) correspond to flat minima, which have been…

Machine Learning · Computer Science 2026-02-17 Rotem Mulayoff , Sebastian U. Stich

The present manuscript presents a framework for automating the formulation and resolution of limit analysis problems in a very general manner. This framework relies on FEniCS domain-specific language and the representation of material…

Optimization and Control · Mathematics 2020-05-12 Jeremy Bleyer , Ghazi Hassen

Recent years have seen advances in generalization bounds for noisy stochastic algorithms, especially stochastic gradient Langevin dynamics (SGLD) based on stability (Mou et al., 2018; Li et al., 2020) and information theoretic approaches…

Machine Learning · Computer Science 2022-11-02 Arindam Banerjee , Tiancong Chen , Xinyan Li , Yingxue Zhou

This work establishes a rigorous connection between stability properties of discrete-time algorithms (DTAs) and corresponding continuous-time dynamical systems derived through $ O(s^r) $-resolution ordinary differential equations (ODEs). We…

Optimization and Control · Mathematics 2026-03-03 Amir Ali Farzin , Yuen-Man Pun , Philipp Braun , Iman Shames

Stochastic gradient descent (SGD) holds as a classical method to build large scale machine learning models over big data. A stochastic gradient is typically calculated from a limited number of samples (known as mini-batch), so it…

Machine Learning · Computer Science 2016-01-14 Yadong Mu , Wei Liu , Wei Fan

In this paper, the stabilized finite element approximation of the Stokes eigenvalue problems is considered for both the two-field (displacement-pressure) and the three-field (stress-displacement-pressure) formulations. The method presented…

Numerical Analysis · Mathematics 2016-09-21 Önder Türk , Daniele Boffi , Ramon Codina

We propose a novel dynamical framework for solving inclusion problems of the form \(0 \in F(x) + G(x)\) in Hilbert spaces, where \(F\) is a maximal set-valued operator and \(G\) is a single-valued mapping. The analysis is conducted under a…

Optimization and Control · Mathematics 2026-01-29 Nam Van Tran

In the context of large-scale networks, the consideration of faults is an evident necessity. This document is focussing on the self-stabilizing approach which aims at conceiving algorithms "repairing themselves" in case of transient faults,…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-10-10 Lélia Blin