Generalized Ellipsoids

We introduce a family of symmetric convex bodies called generalized ellipsoids of degree d (GE-ds), with ellipsoids corresponding to the case of [Formula: see text]. Generalized ellipsoids (GEs) retain many geometric, algebraic, and algorithmic properties of ellipsoids. We show that the conditions that the parameters of a GE must satisfy can be checked in strongly polynomial time and that one can search for GEs of a given degree by solving a semidefinite program whose size grows only linearly with dimension. We give an example of a GE that does not have a second-order cone representation, but we show that every GE has a semidefinite representation whose size depends linearly on both its dimension and its degree. In terms of expressiveness, we prove that for any integer [Formula: see text], every symmetric full-dimensional polytope with 2m facets and every intersection of m cocentered ellipsoids can be represented exactly as a GE-d with [Formula: see text]. Using this result, we show that every symmetric convex body can be approximated arbitrarily well by a GE-d, and we quantify the quality of the approximation as a function of the degree d. Finally, we present applications of GEs to several areas, such as time-varying portfolio optimization, stability analysis of switched linear systems, robust-to-dynamics optimization, and robust polynomial regression. Funding: A. A. Ahmadi was partially supported by the Air Force Office of Scientific Research [Grant MURI], the Sloan Fellowship, and Princeton [AI Lab Seed Grant and SEAS Innovation Grant]. A. Chaudhry was partially supported by the Air Force Office of Scientific Research [Grant MURI].

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Publication Details

Journal
Mathematics of Operations Research
Published
2026-01-30
DOI
https://doi.org/10.1287/moor.2024.0643
Primary Topic
Advanced Optimization Algorithms Research
Type
article
Field-Weighted Citation Impact
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article

Generalized Ellipsoids

Abraar Chaudhry, Cemil Dibek, Amir Ali Ahmadi
Mathematics of Operations Research
Advanced Optimization Algorithms Research
article

Generalized Ellipsoids

Abraar Chaudhry, Cemil Dibek, Amir Ali Ahmadi
article en

Abstract

We introduce a family of symmetric convex bodies called generalized ellipsoids of degree d (GE-ds), with ellipsoids corresponding to the case of [Formula: see text]. Generalized ellipsoids (GEs) retain many geometric, algebraic, and algorithmic properties of ellipsoids. We show that the conditions that the parameters of a GE must satisfy can be checked in strongly polynomial time and that one can search for GEs of a given degree by solving a semidefinite program whose size grows only linearly with dimension. We give an example of a GE that does not have a second-order cone representation, but we show that every GE has a semidefinite representation whose size depends linearly on both its dimension and its degree. In terms of expressiveness, we prove that for any integer [Formula: see text], every symmetric full-dimensional polytope with 2m facets and every intersection of m cocentered ellipsoids can be represented exactly as a GE-d with [Formula: see text]. Using this result, we show that every symmetric convex body can be approximated arbitrarily well by a GE-d, and we quantify the quality of the approximation as a function of the degree d. Finally, we present applications of GEs to several areas, such as time-varying portfolio optimization, stability analysis of switched linear systems, robust-to-dynamics optimization, and robust polynomial regression. Funding: A. A. Ahmadi was partially supported by the Air Force Office of Scientific Research [Grant MURI], the Sloan Fellowship, and Princeton [AI Lab Seed Grant and SEAS Innovation Grant]. A. Chaudhry was partially supported by the Air Force Office of Scientific Research [Grant MURI].

Mathematics of Operations Research
Georgia Institute of Technology (US), Koç University (TR), Princeton University (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 69%
Advanced Optimization Algorithms Research
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