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We introduce GS-PowerHP, a novel zeroth-order method for non-convex optimization problems of the form $\max_{x \in \mathbb{R}^d} f(x)$. Our approach leverages two key components: a power-transformed Gaussian-smoothed surrogate…

Optimization and Control · Mathematics 2025-11-18 Chen Xu

Monotone inclusions have a wide range of applications, including minimization, saddle-point, and equilibria problems. We introduce new stochastic algorithms, with or without variance reduction, to estimate a root of the expectation of…

Optimization and Control · Mathematics 2024-05-24 Abdurakhmon Sadiev , Laurent Condat , Peter Richtárik

We study a class of monotone inclusions called "self-concordant inclusion" which covers three fundamental convex optimization formulations as special cases. We develop a new generalized Newton-type framework to solve this inclusion. Our…

Optimization and Control · Mathematics 2017-07-25 Quoc Tran-Dinh , Tianxiao Sun , Shu Lu

In this paper, a class of optimization problems with nonlinear inequality constraints is discussed. Based on the ideas of sequential quadratic programming algorithm and the method of strongly sub-feasible directions, a new superlinearly…

Optimization and Control · Mathematics 2012-06-28 Jin-Bao Jian , Chuan-Hao Guo , Chun-Ming Tang , Yan-Qin Bai

Let $\Omega$ be a nonempty closed and convex subset of a uniformly smooth and uniformly convex real Banach space $\mathcal{X}$ with dual space $\mathcal{X}^*$. This article presents a hybrid algorithm for finding a common element of the set…

Functional Analysis · Mathematics 2025-09-30 Peter U. Nwokoro , Maria A. Onyido , Markjoe O. Uba , Cyril I. Udeani

We study the convergence rate of the proximal-gradient homotopy algorithm applied to norm-regularized linear least squares problems, for a general class of norms. The homotopy algorithm reduces the regularization parameter in a series of…

Optimization and Control · Mathematics 2016-09-28 Reza Eghbali , Maryam Fazel

Flexible sparsity regularization means stably approximating sparse solutions of operator equations by using coefficient-dependent penalizations. We propose and analyse a general nonconvex approach in this respect, from both theoretical and…

Optimization and Control · Mathematics 2021-11-12 Daria Ghilli , Dirk A. Lorenz , Elena Resmerita

Generally, natural scientific problems are so complicated that one has to establish some effective perturbation or nonperturbation theories with respect to some associated ideal models. In this Letter, a new theory that combines…

Computational Physics · Physics 2015-05-13 Yuan Gao , S. Y. Lou

This work blends the inexact Newton method with iterative combined approximations (ICA) for solving topology optimization problems under the assumption of geometric nonlinearity. The density-based problem formulation is solved using a…

Numerical Analysis · Mathematics 2021-12-17 Thadeu A. Senne , Francisco A. M. Gomes , Sandra A. Santos

In this paper, we propose new algorithms for finding a common point of the solution set of a pseudomonotone equilibrium problem and the set of fixed points of a symmetric generalized hybrid mapping in a real Hilbert space. The convergence…

Optimization and Control · Mathematics 2015-08-18 Bui Van Dinh , Do Sang Kim

Solving a quadratic nonlinear system of equations (QNSE) is a fundamental, but important, task in nonlinear science. We propose an efficient quantum algorithm for solving $n$-dimensional QNSE. Our algorithm embeds QNSE into a…

Quantum Physics · Physics 2022-10-11 Cheng Xue , Xiao-Fan Xu , Yu-Chun Wu , Guo-Ping Guo

In this paper, a method is proposed to solve the problem of monotone smoothing splines using general linear systems. This problem, also called monotone control theoretic splines, has been solved only when the curve generator is modeled by…

Systems and Control · Computer Science 2013-08-08 Masaaki Nagahara , Clyde F. Martin

We introduce Probabilistic Gaussian Homotopy (PGH), a probability-space continuation framework for nonconvex optimization. Unlike classical Gaussian homotopy, which smooths the objective and uniformly averages gradients, PGH deforms the…

Machine Learning · Computer Science 2026-03-17 Eshed Gal , Samy Wu Fung , Eldad Haber

This paper belongs to a group of work in the intersection of symbolic computation and group analysis aiming for the symbolic analysis of differential equations. The goal is to extract important properties without finding the explicit…

Symbolic Computation · Computer Science 2024-01-31 Veronika Treumova , Dmitry A. Lyakhov , Dominik L. Michels

It is well known that Newton's method can have trouble converging if the initial guess is too far from the solution. Such a problem particularly occurs when this method is used to solve nonlinear elliptic partial differential equations…

Numerical Analysis · Mathematics 2024-12-10 Joubine Aghili , Emmanuel Franck , Romain Hild , Victor Michel-Dansac , Vincent Vigon

This paper proposes and develops new Newton-type methods to solve structured nonconvex and nonsmooth optimization problems with justifying their fast local and global convergence by means of advanced tools of variational analysis and…

Optimization and Control · Mathematics 2026-03-03 Pham Duy Khanh , Boris S. Mordukhovich , Vo Thanh Phat

The article introduces a new algorithm for solving a class ofequilibrium problems involving strongly pseudomonotone bifunctions with Lipschitz-type condition. We describe how to incorporate the proximal-like regularized technique with…

Optimization and Control · Mathematics 2018-04-26 Dang Van Hieu

Let $C$ be a nonempty closed and convex subset of a uniformly smooth and uniformly convex real Banach space $E$ with dual space $E^*$. We present a novel hybrid method for finding a common solution of a family of equilibrium problems, a…

Functional Analysis · Mathematics 2022-08-17 Markjoe O. Uba , Maria A. Onyido , Cyril I. Udeani , Peter U. Nwokoro

Finding vacua for the four dimensional effective theories for supergravity which descend from flux compactifications and analyzing them according to their stability is one of the central problems in string phenomenology. Except for some…

High Energy Physics - Theory · Physics 2011-12-15 Dhagash Mehta

While globally optimal solutions to many convex programs can be computed efficiently in polynomial time, this is, in general, not possible for nonconvex optimization problems. Therefore, locally optimal approaches or other efficient…

Information Theory · Computer Science 2020-07-03 Bho Matthiesen , Christoph Hellings , Eduard A. Jorswieck , Wolfgang Utschick
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