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Related papers: Linear optimization over homogeneous matrix cones

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We address the discretization of optimization problems posed on the cone of convex functions, motivated in particular by the principal agent problem in economics, which models the impact of monopoly on product quality. Consider a two…

Numerical Analysis · Mathematics 2014-09-24 Jean-Marie Mirebeau

Statistical problems often involve linear equality and inequality constraints on model parameters. Direct estimation of parameters restricted to general polyhedral cones, particularly when one is interested in estimating low dimensional…

Methodology · Statistics 2025-05-01 Neha Agarwala , Arkaprava Roy , Anindya Roy

Hyperbolicity cones are convex algebraic cones arising from hyperbolic polynomials. A well-understood subclass of hyperbolicity cones is that of spectrahedral cones and it is conjectured that every hyperbolicity cone is spectrahedral. In…

Optimization and Control · Mathematics 2012-08-03 Tim Netzer , Raman Sanyal

We give two characterizations of cones over ellipsoids. Let $C$ be a closed pointed convex linear cone in a finite-dimensional real vector space. We show that $C$ is a cone over an ellipsoid if and only if the affine span of $\partial C…

Metric Geometry · Mathematics 2013-03-08 Jesús Jerónimo-Castro , Tyrrell B. McAllister

An infinite linearly ordered set (S,<=) is called doubly homogeneous if its automorphism group A(S) acts 2-transitively on it. We show that any group G arises as outer automorphism group G cong Out(A(S)) of the automorphism group A(S), for…

Group Theory · Mathematics 2007-05-23 Manfred Droste , Saharon Shelah

We describe strong convex valid inequalities for conic quadratic mixed 0-1 optimization. These inequalities can be utilized for solving numerous practical nonlinear discrete optimization problems from value-at-risk minimization to queueing…

Optimization and Control · Mathematics 2018-08-28 Alper Atamturk , Andres Gomez

Semidefinite programs (SDPs) -- some of the most useful and versatile optimization problems of the last few decades -- are often pathological: the optimal values of the primal and dual problems may differ and may not be attained. Such SDPs…

Optimization and Control · Mathematics 2019-10-23 Gabor Pataki

This work studies the problem of maximizing a higher degree real homogeneous multivariate polynomial over the unit sphere. This problem is equivalent to finding the leading eigenvalue of the associated symmetric tensor of higher order,…

Optimization and Control · Mathematics 2019-10-02 Yuning Yang , Guoyin Li

A successful computational approach for solving large-scale positive semidefinite (PSD) programs is to enforce PSD-ness on only a collection of submatrices. For our study, we let $\mathcal{S}^{n,k}$ be the convex cone of $n\times n$…

Optimization and Control · Mathematics 2021-07-22 Grigoriy Blekherman , Santanu S. Dey , Kevin Shu , Shengding Sun

We study copositive matrices which admit a decomposition into a sum of a positive semidefinite matrix and a matrix with nonnegative entries. Our main result shows that if the off-diagonal entries of a copositive matrix are nondecreasing in…

Optimization and Control · Mathematics 2026-05-18 Grigoriy Blekherman , Santanu S. Dey , Alex Dunbar , Burak Kocuk

We study a nonlinear decomposition of a positive definite matrix into two components: the inverse of another positive definite matrix and a symmetric matrix constrained to lie in a prescribed linear subspace. Equivalently, the inverse…

Optimization and Control · Mathematics 2026-01-27 Yan Dolinsky , Or Zuk

We reformulate the problem of modularity maximization over the set of partitions of a network as a conic optimization problem over the completely positive cone, converting it from a combinatorial optimization problem to a convex continuous…

Data Analysis, Statistics and Probability · Physics 2008-12-18 Roland Hildebrand

Convex optimization is crucial in controlling legged robots, where stability and optimal control are vital. Many control problems can be formulated as convex optimization problems, with a convex cost function and constraints capturing…

Optimization and Control · Mathematics 2023-07-04 Prathamesh Saraf , Mustafa Shaikh , Myron Phan

The basic tool for solving problems in metric geometry and isotonic regression is the metric projection onto closed convex cones. Isotonicity of these projections with respect to a given order relation can facilitate finding the solutions…

Optimization and Control · Mathematics 2016-02-16 A. B. Németh , S. Z. Németh

For those acquainted with CVX (aka disciplined convex programming) of M. Grant and S. Boyd, the motivation of this work is the desire to extend the scope of CVX beyond convex minimization -- to convex-concave saddle point problems and…

Optimization and Control · Mathematics 2021-06-30 Anatoli Juditsky , Arkadi Nemirovski

A vast majority of machine learning algorithms train their models and perform inference by solving optimization problems. In order to capture the learning and prediction problems accurately, structural constraints such as sparsity or low…

Machine Learning · Statistics 2017-12-22 Prateek Jain , Purushottam Kar

This paper addresses the problem of synchronizing orthogonal matrices over directed graphs. For synchronized transformations (or matrices), composite transformations over loops equal the identity. We formulate the synchronization problem as…

Optimization and Control · Mathematics 2017-04-10 Johan Thunberg , Florian Bernard , Jorge Goncalves

The pentablock is a Hartogs domain over the symmetrized bidisc. The domain is a bounded inhomogeneous pseudoconvex domain, and does not have a $\mathcal{C}^{1}$ boundary. Recently, Agler-Lykova-Young constructed a special subgroup of the…

Complex Variables · Mathematics 2014-12-15 Guicong Su , Zhenhan Tu , Lei Wang

In this paper, we study relationships between symmetric and non-symmetric separation of (not necessarily convex) cones by using separating cones of Bishop-Phelps type in real normed spaces. Besides extending some known results for the…

Optimization and Control · Mathematics 2025-09-10 Fernando García-Castaño , Christian Günther , M. A. Melguizo-Padial , Christiane Tammer

A structure is called homogeneous if every isomorphism between finite substructures of the structure extends to an automorphism of the structure. Recently, P. J. Cameron and J. Ne\v{s}et\v{r}il introduced a relaxed version of homogeneity:…

Combinatorics · Mathematics 2010-01-06 Dragan Mašulović , Rajko Nenadov , Nemanja Škorić