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In this paper we study constraint qualifications and optimality conditions for bilevel programming problems. We strive to derive checkable constraint qualifications in terms of problem data and applicable optimality conditions. For the…

Optimization and Control · Mathematics 2019-10-10 Jane J. Ye

We consider two classes of constrained finite state-action stochastic games. First, we consider a two player nonzero sum single controller constrained stochastic game with both average and discounted cost criterion. We consider the same…

Optimization and Control · Mathematics 2012-06-11 Vikas Vikram Singh , N. Hemachandra

We consider a class of optimal control problems that arise in connection with optimal advertising under uncertainty. Two main features appear in the model: a delay in the control variable driving the state dynamics; a mean-field term both…

Optimization and Control · Mathematics 2024-03-04 Michele Ricciardi , Mauro Rosestolato

The main objective of this paper is the construction of the solution of an impulsive stochastic differential equation, subject to control conditions in the pulse-times and give sufficient conditions for them to be random variables with…

Probability · Mathematics 2015-08-24 Ricardo Castro Santis

This paper considers an optimization problem for a dynamical system whose evolution depends on a collection of binary decision variables. We develop scalable approximation algorithms with provable suboptimality bounds to provide…

Optimization and Control · Mathematics 2016-10-31 Insoon Yang , Samuel A. Burden , Ram Rajagopal , S. Shankar Sastry , Claire J. Tomlin

This paper addresses a fundamental and important question in control: under what conditions does there fail to exist a robust control policy that keeps the state of a constrained linear system within a target set, despite bounded…

Systems and Control · Electrical Eng. & Systems 2025-07-08 Paul Trodden , José M. Maestre , Hideaki Ishii

The main purpose of this paper is the study of second-order optimality conditions for the bilinear control of a strongly degenerate parabolic equation. The equation is degenerate at the boundary of the spatial domain. The well-posedness of…

Optimization and Control · Mathematics 2024-11-07 Cyrille Kenne , Landry Djomegne , Pascal Zongo

A new method of deriving comparative statics information using generalized compensated derivatives is presented which yields constraint-free semidefiniteness results for any differentiable, constrained optimization problem. More generally,…

Optimization and Control · Mathematics 2013-10-29 M. Hossein Partovi , Michael R. Caputo

This paper considers a formulation of a differential game with constrained dynamics, where one player selects the dynamics and the other selects the applicable cost. When the game is considered on a finite time horizon, its value satisfies…

Optimization and Control · Mathematics 2009-09-25 Rami Atar , Paul Dupuis

In this paper, we employ a game-theoretic model to analyze the interaction between an adversary and a classifier. There are two classes (i.e., positive and negative classes) to which data points can belong. The adversary is interested in…

Cryptography and Security · Computer Science 2019-06-25 Farhad Farokhi

We consider an extension of a noncooperative game problem where players have joint binding constraints. In this case, justification of a generalized equilibrium point needs a reasonable mechanism for attaining this state. We suggest to…

Optimization and Control · Mathematics 2020-03-24 I. V. Konnov

Learning meaningful representations that maintain the content necessary for a particular task while filtering away detrimental variations is a problem of great interest in machine learning. In this paper, we tackle the problem of learning…

Machine Learning · Computer Science 2018-01-30 Qizhe Xie , Zihang Dai , Yulun Du , Eduard Hovy , Graham Neubig

Maximization and minimization problems of the principle eigenvalue for divergence form second order elliptic operators with the Dirichlet boundary condition are considered. The principal eigen map of such elliptic operators is introduced…

Optimization and Control · Mathematics 2019-08-28 Hongwei Lou , Jiongmin Yong

Affine policies (or control) are widely used as a solution approach in dynamic optimization where computing an optimal adjustable solution is usually intractable. While the worst case performance of affine policies can be significantly bad,…

Optimization and Control · Mathematics 2019-10-15 Omar El Housni , Vineet Goyal

In this paper, we introduce a new second-order directional derivative and a second-order subdifferential of Hadamard type for an arbitrary nondifferentiable function. We derive several second-order optimality conditions for a local and a…

Optimization and Control · Mathematics 2018-05-24 Vsevolod I. Ivanov

This work is concerned with an optimal control problem on a Riemannian manifold, for which two typical cases are considered. The first case is when the endpoint is free. For this case, the control set is assumed to be a separable metric…

Optimization and Control · Mathematics 2016-11-09 Qing Cui , Li Deng , Xu Zhang

We focus on a generalization of the classic Minisum approval voting rule, introduced by Barrot and Lang (2016), and referred to as Conditional Minisum (CMS), for multi-issue elections with preferential dependencies. Under this rule, voters…

Computer Science and Game Theory · Computer Science 2025-06-10 Evangelos Markakis , Georgios Papasotiropoulos

This paper concerns the study of a broad class of minimal time functions corresponding to control problems with constant convex dynamics and closed target sets in arbitrary Banach spaces. In contrast to other publications, we do not impose…

Optimization and Control · Mathematics 2010-09-09 Boris Mordukhovich , Nguyen Mau Nam

Control problems not admitting the dynamic programming principle are known as time-inconsistent. The game-theoretic approach is to interpret such problems as intrapersonal dynamic games and look for subgame perfect Nash equilibria. A…

Optimization and Control · Mathematics 2020-05-04 Kristoffer Lindensjö

The fragility of deep neural networks to adversarially-chosen inputs has motivated the need to revisit deep learning algorithms. Including adversarial examples during training is a popular defense mechanism against adversarial attacks. This…

Optimization and Control · Mathematics 2020-05-05 Jacob H. Seidman , Mahyar Fazlyab , Victor M. Preciado , George J. Pappas