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This review concerns recent results on the quantitative study of convergence towards the stationary state for spatially inhomogeneous kinetic equations. We focus on analytical results obtained by means of certain probabilistic techniques…

Analysis of PDEs · Mathematics 2023-04-05 Havva Yoldaş

We revisit second-order-in-time space-time discretizations of the linear and semilinear wave equations by establishing precise equivalences with first-order-in-time formulations. Focusing on schemes using continuous piecewise-polynomial…

Numerical Analysis · Mathematics 2026-01-07 Matteo Ferrari , Ilaria Perugia , Enrico Zampa

This paper surveys some of our recent progress on Hardy-type inequa\-lities which consist of a well-known topic in Harmonic Analysis. In the first section, we recall the original probabilistic motivation dealing with the stability speed in…

Probability · Mathematics 2014-12-02 Mu-Fa Chen

Homogeneous relaxation is a ubiquitous phenomenon in semiclassical kinetic theories where the quasiparticles are distributed uniformly in space, and the equilibration involves only their velocity distribution. For such solutions, the…

High Energy Physics - Theory · Physics 2015-03-19 Ramakrishnan Iyer , Ayan Mukhopadhyay

The success of adversarial formulations in machine learning has brought renewed motivation for smooth games. In this work, we focus on the class of stochastic Hamiltonian methods and provide the first convergence guarantees for certain…

We study convergence to equilibrium of the linear relaxation Boltzmann (also known as linear BGK) and the linear Boltzmann equations either on the torus $(x,v) \in \mathbb{T}^d \times \mathbb{R}^d$ or on the whole space $(x,v) \in…

Analysis of PDEs · Mathematics 2020-11-10 José A. Cañizo , Chuqi Cao , Josephine Evans , Havva Yoldaş

We use the semi-discrete method, originally proposed in Halidias (2012), Semi-discrete approximations for stochastic differential equations and applications, International Journal of Computer Mathematics, 89(6), to reproduce qualitative…

Numerical Analysis · Mathematics 2017-08-29 Ioannis S. Stamatiou

Stochastic Gradient Descent (SGD) is widely used in machine learning research. Previous convergence analyses of SGD under the vanishing step-size setting typically require Robbins-Monro conditions. However, in practice, a wider variety of…

Machine Learning · Computer Science 2025-04-18 Ruinan Jin , Difei Cheng , Hong Qiao , Xin Shi , Shaodong Liu , Bo Zhang

The paper proposes a novel hybrid method for solving equilibrium problems and fixed point problems. By constructing specially cutting-halfspaces, in this algorithm, only an optimization program is solved at each iteration without the…

Optimization and Control · Mathematics 2015-10-30 Dang Van Hieu

The solutions of Hamiltonian equations are known to describe the underlying phase space of a mechanical system. In this article, we propose a novel spatio-temporal model using a strategic modification of the Hamiltonian equations,…

Methodology · Statistics 2026-02-17 Satyaki Mazumder , Sayantan Banerjee , Sourabh Bhattacharya

Based on the well-established theory of discrete conjugate nets in discrete differential geometry, we propose and examine discrete analogues of important objects and notions in the theory of semi-Hamiltonian systems of hydrodynamic type. In…

Exactly Solvable and Integrable Systems · Physics 2015-06-23 B. G. Konopelchenko , W. K. Schief

We propose a new discretization method for the Stokes equations. The method is an improved version of the method recently presented in [C. Lehrenfeld, J. Sch\"oberl, Comp. Meth. Appl. Mech. Eng., 361 (2016)] which is based on an…

Numerical Analysis · Mathematics 2018-03-29 Philip L. Lederer , Christoph Lehrenfeld , Joachim Schöberl

We consider Hamiltonian systems with symmetry, and relative equilibria with isotropy subgroup of positive dimension. The stability of such relative equilibria has been studied by Ortega and Ratiu and by Lerman and Singer. In both papers the…

Dynamical Systems · Mathematics 2015-05-20 James Montaldi , Miguel Rodriguez-Olmos

For a bar-joint framework $(G,p)$, a subgroup $\Gamma$ of the automorphism group of $G$, and a subgroup of the orthogonal group isomorphic to $\Gamma$, we introduce a symmetric averaging map which produces a bar-joint framework on $G$ with…

Metric Geometry · Mathematics 2025-02-24 Cameron Millar , Bernd Schulze , Louis Theran

In this paper we consider Tyler's robust covariance M-estimator under group symmetry constraints. We assume that the covariance matrix is invariant to the conjugation action of a unitary matrix group, referred to as group symmetry. Examples…

Applications · Statistics 2015-09-30 Ilya Soloveychik , Dmitry Trushin , Ami Wiesel

We investigate the large time behavior of solutions to the spatially homogeneous linear Boltzmann equation from a semigroup viewpoint. Our analysis is performed in some (weighted) $L^{1}$-spaces. We deal with both the cases of hard and soft…

Analysis of PDEs · Mathematics 2015-10-09 Bertrand Lods , Mustapha Mokhtar-Kharroubi

We consider the stable matching problem when the preference lists are not given explicitly but are represented in a succinct way and ask whether the problem becomes computationally easier and investigate other implications. We give…

Data Structures and Algorithms · Computer Science 2016-12-21 Marvin Künnemann , Daniel Moeller , Ramamohan Paturi , Stefan Schneider

We carry out a stability and convergence analysis of a fully discrete scheme for the time-dependent Navier-Stokes equations resulting from combining an $H(\mathrm{div}, \Omega)$-conforming discontinuous Galerkin spatial discretization, and…

Numerical Analysis · Mathematics 2025-10-22 L. Beirão da Veiga , F. Dassi , S. Gómez

A proof of convergence is given for bulk--surface finite element semi-discretisation of the Cahn--Hilliard equation with Cahn--Hilliard-type dynamic boundary conditions in a smooth domain. The semi-discretisation is studied in the weak…

Numerical Analysis · Mathematics 2020-12-01 Paula Harder , Balázs Kovács

Entropic optimal transport problems play an increasingly important role in machine learning and generative modelling. In contrast with optimal transport maps which often have limited applicability in high dimensions, Schrodinger bridges can…

Probability · Mathematics 2026-01-21 Pierre Del Moral , Ajay Jasra
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