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We present a numerical method for the minimization of objectives that are augmented with large quadratic penalties of overdetermined inconsistent equality constraints. Such objectives arise from quadratic integral penalty methods for the…

Optimization and Control · Mathematics 2020-09-15 Martin P. Neuenhofen , Eric C. Kerrigan

How heterogeneous multiscale methods (HMM) handle fluctuations acting on the slow variables in fast-slow systems is investigated. In particular, it is shown via analysis of central limit theorems (CLT) and large deviation principles (LDP)…

Probability · Mathematics 2016-01-12 David Kelly , Eric Vanden-Eijnden

In this paper we bring together the method of Lagrangian descriptors and the principle of least action, or more precisely, of stationary action, in both deterministic and stochastic settings. In particular, we show how the action can be…

Dynamical Systems · Mathematics 2024-03-06 V. J. García-Garrido , S. Wiggins

First-order methods (FOMs) have been widely used for solving large-scale problems. A majority of existing works focus on problems without constraint or with simple constraints. Several recent works have studied FOMs for problems with…

Optimization and Control · Mathematics 2021-02-10 Zichong Li , Yangyang Xu

ALAMO is a computational methodology for leaning algebraic functions from data. Given a data set, the approach begins by building a low-complexity, linear model composed of explicit non-linear transformations of the independent variables.…

Machine Learning · Computer Science 2017-06-01 Zachary T. Wilson , Nikolaos V. Sahinidis

This paper proposes a homotopy coordinate descent (HCD) method to solve the $l_0$-norm regularized least square ($l_0$-LS) problem for compressed sensing, which combine the homotopy technique with a variant of coordinate descent method.…

Machine Learning · Computer Science 2020-11-16 Zhenzhen Sun , Yuanlong Yu

State-of-the-art techniques for simultaneous localization and mapping (SLAM) employ iterative nonlinear optimization methods to compute an estimate for robot poses. While these techniques often work well in practice, they do not provide…

Robotics · Computer Science 2015-07-21 Luca Carlone , David Rosen , Giuseppe Calafiore , John Leonard , Frank Dellaert

The so-called ``small denominator problem'' was a fundamental problem of dynamics, as pointed out by Poincar\'{e}. Small denominators appear most commonly in perturbative theory. The Duffing equation is the simplest example of a…

Classical Physics · Physics 2023-01-11 Shijun Liao

This article deals with the adaptive and approximative computation of the Lam\'e equations. The equations of linear elasticity are considered as boundary integral equations and solved in the setting of the boundary element method (BEM).…

Numerical Analysis · Mathematics 2022-05-11 Maximilian Bauer , Mario Bebendorf

This work presents an adaptive superfast proximal augmented Lagrangian (AS-PAL) method for solving linearly-constrained smooth nonconvex composite optimization problems. Each iteration of AS-PAL inexactly solves a possibly nonconvex…

Optimization and Control · Mathematics 2022-10-07 Arnesh Sujanani , Renato D. C. Monteiro

In this paper, the hybrid sparse/diffuse (HSD) channel model in frequency domain is proposed. Based on the structural analysis on the resolvable paths and diffuse scattering statistics in the channel, the Hybrid Atomic-Least-Squares (HALS)…

Signal Processing · Electrical Eng. & Systems 2025-09-16 Lei Lyu , Urbashi Mitra

A least action principle for damping motion has been previously proposed with a Hamiltonian and a Lagrangian containing the energy dissipated by friction. Due to the space-time nonlocality of the Lagrangian, mathematical uncertainties…

Classical Physics · Physics 2014-12-03 Tongling Lin , Qiuping A. Wang

We propose NAMA (Newton-type Alternating Minimization Algorithm) for solving structured nonsmooth convex optimization problems where the sum of two functions is to be minimized, one being strongly convex and the other composed with a linear…

Optimization and Control · Mathematics 2019-11-11 Lorenzo Stella , Andreas Themelis , Panagiotis Patrinos

The Gaussian homotopy (GH) method is a popular approach to finding better stationary points for non-convex optimization problems by gradually reducing a parameter value $t$, which changes the problem to be solved from an almost convex one…

Optimization and Control · Mathematics 2022-11-17 Hidenori Iwakiri , Yuhang Wang , Shinji Ito , Akiko Takeda

First-order methods have been studied for nonlinear constrained optimization within the framework of the augmented Lagrangian method (ALM) or penalty method. We propose an improved inexact ALM (iALM) and conduct a unified analysis for…

Optimization and Control · Mathematics 2021-03-25 Zichong Li , Pin-Yu Chen , Sijia Liu , Songtao Lu , Yangyang Xu

Energy minimization algorithms, such as graph cuts, enable the computation of the MAP solution under certain probabilistic models such as Markov random fields. However, for many computer vision problems, the MAP solution under the model is…

Computer Vision and Pattern Recognition · Computer Science 2013-07-31 Yongsub Lim , Kyomin Jung , Pushmeet Kohli

This work investigates the convergence behavior of augmented Lagrangian methods (ALMs) when applied to convex optimization problems that may be infeasible. ALMs are a popular class of algorithms for solving constrained optimization…

Optimization and Control · Mathematics 2026-03-17 Roland Andrews , Justin Carpentier , Adrien Taylor

The explicit analytic solution of the Thomas Fermi equation thorough a new kind of analytic technique, namely the homotopy analysis method, was employed by Liao (Appl. Math. Comp. 144, (2003)). However, the base functions and the auxiliary…

Mathematical Physics · Physics 2009-09-08 M. Turkyilmazoglu

In a real Hilbert space setting, we reconsider the classical Arrow-Hurwicz differential system in view of solving linearly constrained convex minimization problems. We investigate the asymptotic properties of the differential system and…

Optimization and Control · Mathematics 2023-01-03 Simon K. Niederländer

This paper introduces HALLaR, a new first-order method for solving large-scale semidefinite programs (SDPs) with bounded domain. HALLaR is an inexact augmented Lagrangian (AL) method where the AL subproblems are solved by a novel hybrid…

Optimization and Control · Mathematics 2024-03-19 Renato D. C. Monteiro , Arnesh Sujanani , Diego Cifuentes