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A common problem to all applications of linear finite dynamical systems is analyzing the dynamics without enumerating every possible state transition. Of particular interest is the long term dynamical behaviour. In this paper, we study the…

Dynamical Systems · Mathematics 2019-04-01 Björn Lindenberg

We revisit the smooth convex-concave bilinearly-coupled saddle-point problem of the form $\min_x\max_y f(x) + \langle y,\mathbf{B} x\rangle - g(y)$. In the highly specific case where each of the functions $f(x)$ and $g(y)$ is either affine…

Optimization and Control · Mathematics 2024-11-25 Dmitry Kovalev , Ekaterina Borodich

We derive stability criteria for saddle points of a class of nonsmooth optimization problems in Hilbert spaces arising in PDE-constrained optimization, using metric regularity of infinite-dimensional set-valued mappings. A main ingredient…

Optimization and Control · Mathematics 2017-02-13 Christian Clason , Tuomo Valkonen

In this paper, we introduce some adaptive methods for solving variational inequalities with relatively strongly monotone operators. Firstly, we focus on the modification of the recently proposed, in smooth case [1], adaptive numerical…

Optimization and Control · Mathematics 2022-11-01 A. A. Titov , S. S. Ablaev , M. S. Alkousa , F. S. Stonyakin , A. V. Gasnikov

In this paper, we study the lower iteration complexity bounds for finding the saddle point of a strongly convex and strongly concave saddle point problem: $\min_x\max_yF(x,y)$. We restrict the classes of algorithms in our investigation to…

Optimization and Control · Mathematics 2021-06-22 Junyu Zhang , Mingyi Hong , Shuzhong Zhang

Fine-tuning a pre-trained model (such as BERT, ALBERT, RoBERTa, T5, GPT, etc.) has proven to be one of the most promising paradigms in recent NLP research. However, numerous recent works indicate that fine-tuning suffers from the…

Machine Learning · Computer Science 2023-12-08 Zihao Fu , Anthony Man-Cho So , Nigel Collier

In this paper, we propose a variance-reduced primal-dual algorithm with Bregman distance for solving convex-concave saddle-point problems with finite-sum structure and nonbilinear coupling function. This type of problems typically arises in…

Optimization and Control · Mathematics 2021-06-02 Erfan Yazdandoost Hamedani , Afrooz Jalilzadeh

The state-of-the art proof of a global inf-sup condition on mixed finite element schemes does not allow for an analysis of truly indefinite, second-order linear elliptic PDEs. This paper, therefore, first analyses a nonconforming finite…

Numerical Analysis · Mathematics 2014-01-21 Carsten Carstensen , Asha K. Dond , Neela Nataraj , Amiya K. Pani

This paper discusses a so-called ultra-weak three-field formulation of the biharmonic problem where the solution, its gradient, and an additional Lagrange multiplier are the three unknowns. We establish the well-posedness of the problem…

Numerical Analysis · Mathematics 2026-02-02 Rekha Khot , Bishnu P. Lamichhane , Ricardo Ruiz-Baier

The problem of increasing the accuracy of an approximate solution is considered for boundary value problems for parabolic equations. For ordinary differential equations (ODEs), nonstandard finite difference schemes are in common use for…

Numerical Analysis · Computer Science 2017-05-22 Petr N. Vabishchevich

The first order condition of the constrained minimization problem leads to a saddle point problem. A multigrid method using a multiplicative Schwarz smoother for saddle point problems can thus be interpreted as a successive subspace…

Numerical Analysis · Mathematics 2016-01-19 Long Chen

This paper proposes an asymmetric perturbation technique for solving bilinear saddle-point optimization problems, commonly arising in minimax problems, game theory, and constrained optimization. Perturbing payoffs or values is known to be…

Optimization and Control · Mathematics 2026-02-16 Kenshi Abe , Mitsuki Sakamoto , Kaito Ariu , Atsushi Iwasaki

Based on G. Lan's accelerated gradient sliding and general relation between the smoothness and strong convexity parameters of function under Legendre transformation we show that under rather general conditions the best known bounds for…

Optimization and Control · Mathematics 2020-01-03 Mohammad Alkousa , Darina Dvinskikh , Fedor Stonyakin , Alexander Gasnikov , Dmitry Kovalev

This paper focuses on stochastic saddle point problems with decision-dependent distributions. These are problems whose objective is the expected value of a stochastic payoff function and whose data distribution drifts in response to…

Optimization and Control · Mathematics 2022-11-15 Killian Wood , Emiliano Dall'Anese

We study the performance of stochastic first-order methods for finding saddle points of convex-concave functions. A notorious challenge faced by such methods is that the gradients can grow arbitrarily large during optimization, which may…

Machine Learning · Computer Science 2024-06-10 Gergely Neu , Nneka Okolo

We study a non standard mixed formulation of the Poisson problem, sometimes known as dual mixed formulation. For reasons related to the equilibration of the flux, we use finite elements that are conforming in H(div) for the approximation of…

Numerical Analysis · Mathematics 2022-10-24 Fleurianne Bertrand , Daniele Boffi

Fourth-order differential equations play an important role in many applications in science and engineering. In this paper, we present a three-field mixed finite-element formulation for fourth-order problems, with a focus on the effective…

Numerical Analysis · Mathematics 2022-10-13 Patrick E. Farrell , Abdalaziz Hamdan , Scott P. MacLachlan

We propose an algorithm to numerically determined whether a second-order linear PDE problem satisfying a Garding inequality is well-posed. This algorithm further provides a lower bound to the inf-sup constant of the weak formulation, which…

Numerical Analysis · Mathematics 2026-05-20 T. Chaumont-Frelet

We use the practical framework for abstract perturbed saddle point problems recently introduced by Hong et al. to analyze the mixed formulation of the Hodge Laplace problem. We compose two parameter-dependent norms in which the uniform…

Numerical Analysis · Mathematics 2025-08-01 Wietse M. Boon , Johannes Kraus , Tomáš Luber , Maria Lymbery

We present a novel accelerated primal-dual (APD) method for solving a class of deterministic and stochastic saddle point problems (SPP). The basic idea of this algorithm is to incorporate a multi-step acceleration scheme into the…

Optimization and Control · Mathematics 2013-09-24 Yunmei Chen , Guanghui Lan , Yuyuan Ouyang