K. Anstreicher

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20202026

most citedQuadratic Optimization with Switching Variables: The Convex Hull for

n = 2

1 citations · 1 across the 4 of their papers we have counts for

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math.OC2026

New insights into the NLP-Id bound for maximum-entropy sampling

Kurt Anstreicher, Marcia Fampa, Jon Lee +2

We establish new properties of the NLP-Id upper bound for the maxi\-mum-entropy sampling problem (MESP). In particular, we give a detailed look at the concavity of its objective fu…

math.OC2026

Extended-variable relaxations for the constrained generalized maximum-entropy sampling problem

Gabriel Ponte, Kurt Anstreicher, Marcia Fampa +1

The constrained generalized maximum-entropy sampling problem (CGMESP) is to select an order-s principal submatrix from an order-n covariance matrix, subject to some linear side con…

math.OC2025

Extended Triangle Inequalities for Nonconvex Box-Constrained Quadratic Programming

Kurt M. Anstreicher, Diane Puges

Let $Box_{n} = {x \in R^{n} : 0 \leq x \leq e}$ , and let $QPB_{n}$ denote the convex hull of ${(1, x^{'})^{'} (1, x^{'}) : x \in Box_{n}}$ . The quadratic programming pro…

math.OC2020

Convex Hull Representations for Bounded Products of Variables

Kurt M. Anstreicher, Samuel Burer, Kyungchan Park

It is well known that the convex hull of ${(x, y, x y)}$ , where $(x, y)$ is constrained to lie in a box, is given by the Reformulation-Linearization Technique (RLT) constraints. Belo…

math.OC2020★ 1 cited

Quadratic Optimization with Switching Variables: The Convex Hull for $n = 2$

Samuel Burer, Kurt Anstreicher

We consider quadratic optimization in variables $(x, y)$ where $0 \leq x \leq y$ , and $y \in {0, 1}^{n}$ . Such binary $y$ are commonly refered to as "indicator" or "switching" variables an…