6 citations · 15 across the 11 of their papers we have counts for
13 papers
Applications of the Lorentz positive cone in nonconvex quadratic optimization
Samuel Burer, Kurt Anstreicher
We consider the Lorentz positive cone of matrices that map the Lorentz cone in $\Rbb^m$ into the Lorentz cone in $\Rbb^n$. The Lorentz positive cone and its dual, the c…
Optimization of a Triangular Delaunay Mesh Generator using Reinforcement Learning
Will Thacher, Per-Olof Persson, Yulong Pan
In this work we introduce a triangular Delaunay mesh generator that can be trained using reinforcement learning to maximize a given mesh quality metric. Our mesh generator consists…
A Slightly Lifted Convex Relaxation for Nonconvex Quadratic Programming with Ball Constraints
Samuel Burer
Globally optimizing a nonconvex quadratic over the intersection of balls in is known to be polynomial-time solvable for fixed . Moreover, when , the stan…
A Strengthened SDP Relaxation for Quadratic Optimization Over the Stiefel Manifold
Samuel Burer, Kyungchan Park
We study semidefinite programming (SDP) relaxations for the NP-hard problem of globally optimizing a quadratic function over the Stiefel manifold. We introduce a strengthened relax…
A Semidefinite Relaxation for Sums of Heterogeneous Quadratic Forms on the Stiefel Manifold
Kyle Gilman, Sam Burer, Laura Balzano
We study the maximization of sums of heterogeneous quadratic forms over the Stiefel manifold, a nonconvex problem that arises in several modern signal processing and machine learni…
Strengthened SDP Relaxation for an Extended Trust Region Subproblem with an Application to Optimal Power Flow
Anders Eltved, Samuel Burer
We study an extended trust region subproblem minimizing a nonconvex function over the hollow ball intersected with a full-dimensional second order cone (SOC) co…
Convex Hull Representations for Bounded Products of Variables
Kurt M. Anstreicher, Samuel Burer, Kyungchan Park
It is well known that the convex hull of , where is constrained to lie in a box, is given by the Reformulation-Linearization Technique (RLT) constraints. Belo…
Quadratic Optimization with Switching Variables: The Convex Hull for
Samuel Burer, Kurt Anstreicher
We consider quadratic optimization in variables where , and . Such binary are commonly refered to as "indicator" or "switching" variables an…
Exact Semidefinite Formulations for a Class of (Random and Non-Random) Nonconvex Quadratic Programs
Samuel Burer, Yinyu Ye
We study a class of quadratically constrained quadratic programs (QCQPs), called {\em diagonal QCQPs\/}, which contain no off-diagonal terms for , and we provide…
A Data-Driven Distributionally Robust Bound on the Expected Optimal Value of Uncertain Mixed 0-1 Linear Programming
Guanglin Xu, Samuel Burer
This paper studies the expected optimal value of a mixed 0-1 programming problem with uncertain objective coefficients following a joint distribution. We assume that the true distr…
A Copositive Approach for Two-Stage Adjustable Robust Optimization with Uncertain Right-Hand Sides
Guanglin Xu, Samuel Burer
We study two-stage adjustable robust linear programming in which the right-hand sides are uncertain and belong to a convex, compact uncertainty set. This problem is NP-hard, and th…
Robust Sensitivity Analysis of the Optimal Value of Linear Programming
Guanglin Xu, Samuel Burer
We propose a framework for sensitivity analysis of linear programs (LPs) in minimization form, allowing for simultaneous perturbations in the objective coefficients and right-hand…
How to Convexify the Intersection of a Second Order Cone and a Nonconvex Quadratic
Sam Burer, Fatma Kilinc-Karzan
A recent series of papers has examined the extension of disjunctive-programming techniques to mixed-integer second-order-cone programming. For example, it has been shown---by sever…