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This paper focuses on stochastic methods for solving smooth non-convex strongly-concave min-max problems, which have received increasing attention due to their potential applications in deep learning (e.g., deep AUC maximization,…

Machine Learning · Computer Science 2023-04-19 Zhishuai Guo , Yan Yan , Zhuoning Yuan , Tianbao Yang

We maximize the production of biogas in a gradostat at steady state. The physical decision variables are the water, substrate, and biomass entering each tank and the flows through the interconnecting pipes. Our main technical focus is the…

Optimization and Control · Mathematics 2021-02-04 Josh Taylor , Alain Rapaport

This work is a continuation of the previous one in [{\it Optimization} (2023)], where the existence of optimal solutions and first-order necessary optimality conditions in both Pontryagin's maximum principle form and the variational form…

Optimization and Control · Mathematics 2024-10-01 Cung The Anh , Nguyen Hai Ha Giang

Many scientific and engineering applications feature nonsmooth convex minimization problems over convex sets. In this paper, we address an important instance of this broad class where we assume that the nonsmooth objective is equipped with…

Optimization and Control · Mathematics 2014-06-23 Quoc Tran Dinh , Anastasios Kyrillidis , Volkan Cevher

We develop two new variants of alternating direction methods of multipliers (ADMM) and two parallel primal-dual decomposition algorithms to solve a wide range class of constrained convex optimization problems. Our approach relies on a novel…

Optimization and Control · Mathematics 2018-06-15 Quoc Tran-Dinh , Yuzixuan Zhu

This paper is concerned with the derivation of necessary conditions for the optimal shape of a design problem governed by a non-smooth PDE. The main particularity thereof is the lack of differentiability of the nonlinearity in the state…

Optimization and Control · Mathematics 2024-09-24 Livia Betz

In this paper, using an optimal partition approach, we study the parametric analysis of a second-order conic optimization problem, where the objective function is perturbed along a fixed direction. We characterize the notions of so-called…

Optimization and Control · Mathematics 2021-06-11 Ali Mohammad-Nezhad , Tamas Terlaky

We study local controllability and optimal control problems for invertible discrete-time control systems. We present second order necessary conditions for optimality and sufficient conditions for local controllability. The conditions are…

Optimization and Control · Mathematics 2013-01-30 M. Barbero-Liñán , B. Jakubczyk

We investigate the continuous non-monotone DR-submodular maximization problem subject to a down-closed convex solvable constraint. Our first contribution is to construct an example to demonstrate that (first-order) stationary points can…

Data Structures and Algorithms · Computer Science 2024-03-27 Shengminjie Chen , Donglei Du , Wenguo Yang , Dachuan Xu , Suixiang Gao

This paper considers a nonconvex optimization problem that evolves over time, and addresses the synthesis and analysis of regularized primal-dual gradient methods to track a Karush-Kuhn-Tucker (KKT) trajectory. The proposed regularized…

Optimization and Control · Mathematics 2018-12-04 Yujie Tang , Emiliano Dall'Anese , Andrey Bernstein , Steven Low

This paper presents an algorithm to solve non-convex optimal control problems, where non-convexity can arise from nonlinear dynamics, and non-convex state and control constraints. This paper assumes that the state and control constraints…

Optimization and Control · Mathematics 2017-05-05 Yuanqi Mao , Michael Szmuk , Behcet Acikmese

The interaction of relativistically intense lasers with opaque targets represents a highly non-linear, multi-dimensional parameter space. This limits the utility of sequential 1D scanning of experimental parameters for the optimisation of…

This paper presents a convex optimization-based method for finding the globally optimal solutions of a class of mixed-integer non-convex optimal control problems. We consider problems that are non-convex in the input norm, which is a…

Optimization and Control · Mathematics 2019-11-20 Danylo Malyuta , Michael Szmuk , Behcet Acikmese

The paper is devoted to a comprehensive study of composite models in variational analysis and optimization the importance of which for numerous theoretical, algorithmic, and applied issues of operations research is difficult to overstate.…

Optimization and Control · Mathematics 2019-12-10 Ashkan Mohammadi , Boris S. Mordukhovich , M. Ebrahim Sarabi

We propose two new alternating direction methods to solve "fully" nonsmooth constrained convex problems. Our algorithms have the best known worst-case iteration-complexity guarantee under mild assumptions for both the objective residual and…

Optimization and Control · Mathematics 2018-01-16 Quoc Tran-Dinh , Volkan Cevher

Second-order necessary optimality conditions for nonlinear conic programming problems that depend on a single Lagrange multiplier are usually built under nondegeneracy and strict complementarity. In this paper we establish a condition of…

Optimization and Control · Mathematics 2022-08-08 Ellen H. Fukuda , Gabriel Haeser , Leonardo M. Mito

In this paper, we derive explicit second-order necessary and sufficient optimality conditions of a local minimizer to an optimal control problem for a quasilinear second-order partial differential equation with a piecewise smooth but not…

Optimization and Control · Mathematics 2023-09-13 Christian Clason , Vu Huu Nhu , Arnd Rösch

We provide a correction to the sufficient conditions under which closed-form expressions for the optimal Lagrange multiplier are provided in arXiv:2112.13138 [math.OC]. We first present a simple counterexample where the original conditions…

Optimization and Control · Mathematics 2025-03-13 Henri Lefebvre , Anirudh Subramanyam

We consider shape optimization problems subject to elliptic partial differential equations. In the context of the finite element method, the geometry to be optimized is represented by the computational mesh, and the optimization proceeds by…

Optimization and Control · Mathematics 2019-07-12 Tommy Etling , Roland Herzog , Estefanía Loayza , Gerd Wachsmuth

Successive quadratic approximations, or second-order proximal methods, are useful for minimizing functions that are a sum of a smooth part and a convex, possibly nonsmooth part that promotes regularization. Most analyses of iteration…

Optimization and Control · Mathematics 2019-01-25 Ching-pei Lee , Stephen J. Wright