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Binary quadratic programming problems have attracted much attention in the last few decades due to their potential applications. This type of problems are NP-hard in general, and still considered a challenge in the design of efficient…

Data Structures and Algorithms · Computer Science 2014-11-20 Khaled Elbassioni , Trung Thanh Nguyen

We show that the Mordukhovich-stationarity system associated with a mathematical program with complementarity constraints (MPCC) can be equivalently written as a system of discontinuous equations which can be tackled with a semismooth…

Optimization and Control · Mathematics 2020-11-03 Felix Harder , Patrick Mehlitz , Gerd Wachsmuth

This paper introduces a computationally efficient method that converges globally to B-stationary points of mathematical programs with equilibrium constraints (MPECs). B-stationarity is necessary for optimality and means that no feasible…

Optimization and Control · Mathematics 2026-03-13 Armin Nurkanović , Sven Leyffer

This paper focuses on the error bounds for several equivalent rank-one doubly nonnegative (DNN) conic reformulations of the quadratic assignment problem (QAP), a class of challenging combinatorial optimization problems. We provide three…

Optimization and Control · Mathematics 2025-10-08 Yitian Qian , Shaohua Pan , Shujun Bi , Houduo Qi

Using a new definition for the nonlinear term, we prove that all weak solutions to the SQG equation (and mSQG) conserve the angular momentum. This result is new for the weak solutions of [Resnick, '95] and rules out the possibility of…

Analysis of PDEs · Mathematics 2024-03-14 Philip Isett , Andrew Ma

We investigate two new optimization problems -- minimizing a submodular function subject to a submodular lower bound constraint (submodular cover) and maximizing a submodular function subject to a submodular upper bound constraint…

Data Structures and Algorithms · Computer Science 2013-11-12 Rishabh Iyer , Jeff Bilmes

This paper is devoted to the theoretical and numerical investigation of an augmented Lagrangian method for the solution of optimization problems with geometric constraints. Specifically, we study situations where parts of the constraints…

Optimization and Control · Mathematics 2022-04-20 Xiaoxi Jia , Christian Kanzow , Patrick Mehlitz , Gerd Wachsmuth

We show that the training problem of a deep linear neural network under the squared loss admits an exact convex reformulation in a lifted space over a generalized completely positive cone. The reformulation has the same optimal value as the…

Machine Learning · Computer Science 2026-05-19 Karthik Prakhya , Alp Yurtsever

We study disjunctive conic sets involving a general regular (closed, convex, full dimensional, and pointed) cone K such as the nonnegative orthant, the Lorentz cone or the positive semidefinite cone. In a unified framework, we introduce…

Optimization and Control · Mathematics 2015-04-02 Fatma Kılınç-Karzan

Sequential optimality conditions play an important role in constrained optimization since they provide necessary conditions without requiring constraint qualifications (CQs). This paper introduces a second-order extension of the Approximate…

Optimization and Control · Mathematics 2025-07-30 Huimin Li , Yuya Yamakawa , Ellen H. Fukuda

This is the report-version of a mini-series of two articles on the foundations of satisfiability of conjunctive normal forms with non-boolean variables, to appear in Fundamenta Informaticae, 2011. These two parts are here bundled in one…

Discrete Mathematics · Computer Science 2012-02-15 Oliver Kullmann

The aim of this paper is to address an open problem given in [Kirk, W. A., Shahzad, Naseer, Normal structure and orbital fixed point conditions, J. Math. Anal. Appl. {\bf{vol 463(2)}}, (2018) 461--476]. We give a characterization of weak…

Functional Analysis · Mathematics 2022-01-27 Abhik Digar , Rafael Espínola García , G. Sankara Raju Kosuru

This paper solves a fundamental open problem in variational analysis on the equivalence between the Aubin property and the strong regularity for nonlinear second-order cone programming (SOCP) at a locally optimal solution. We achieve this…

Optimization and Control · Mathematics 2025-01-08 Liang Chen , Ruoning Chen , Defeng Sun , Junyuan Zhu

Second-order Moller-Plesset perturbation theory (MP2) for ab initio simulations of solids is often limited by divergence or over-correlation issues, particularly in metallic, narrow-gap, and dispersion-stabilized systems. We develop and…

Materials Science · Physics 2025-10-28 Meng-Fu Chen , Jinghong Zhang , Hieu Q. Dinh , Adam Rettig , Joonho Lee

It is well-known that the quadratic convex reformulation (QCR) technique can speed up some general-purpose solvers such as CPLEX and Gurobi. Recently, the method of quadratic nonconvex reformulation (QNR) was proposed, which provides an…

Optimization and Control · Mathematics 2026-02-24 Cheng Lu , Yu Fei , Jing Zhou , Zhibin Deng , Guangtai Qu

A recent trend in object oriented (OO) programming languages is the use of Access Permissions (APs) as an abstraction for controlling concurrent executions of programs. The use of AP source code annotations defines a protocol specifying how…

Logic in Computer Science · Computer Science 2018-02-14 Carlos Olarte , Elaine Pimentel , Camilo Rueda

Recently the Master Constraint Programme for Loop Quantum Gravity (LQG) was proposed as a classically equivalent way to impose the infinite number of Wheeler -- DeWitt constraint equations in terms of a single Master Equation. While the…

General Relativity and Quantum Cosmology · Physics 2009-11-10 Bianca Dittrich , Thomas Thiemann

We analyze an optimal stopping problem with a series of inequality-type and equality-type expectation constraints in a general non-Markovian framework. We show that the optimal stopping problem with expectation constraints (OSEC) in an…

Optimization and Control · Mathematics 2023-02-10 Erhan Bayraktar , Song Yao

This paper mainly concerns with the primal superlinear convergence of the quasi-Newton sequential quadratic programming (SQP) method for piecewise linear-quadratic composite optimization problems. We show that the latter primal superlinear…

Optimization and Control · Mathematics 2021-01-01 Ebrahim Sarabi

We establish strong duality relations for functional two-step compositional risk-constrained learning problems with multiple nonconvex loss functions and/or learning constraints, regardless of nonconvexity and under a minimal set of…

Machine Learning · Computer Science 2023-12-05 Dionysis Kalogerias , Spyridon Pougkakiotis
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