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In this paper, we present a unified analysis of matrix completion under general low-dimensional structural constraints induced by {\em any} norm regularization. We consider two estimators for the general problem of structured matrix…

Machine Learning · Statistics 2018-11-26 Suriya Gunasekar , Arindam Banerjee , Joydeep Ghosh

We consider the optimal transport problem over convex costs arising from optimal control of linear time-invariant(LTI) systems when the initial and target measures are assumed to be supported on the set of equilibrium points of the LTI…

Optimization and Control · Mathematics 2023-12-19 Karthik Elamvazhuthi , Matt Jacobs

We discuss conditions under which a convex cone $\K\subset \R^{\Omega}$ admits a probability $m$ such that $\sup_{k\in \K} m(k)\leq0$. Based on these, we also characterize linear functionals that admit the representation as finitely…

Functional Analysis · Mathematics 2021-03-26 Gianluca Cassese

Consider the closed convex hull $K$ of a monomial curve given parametrically as $(t^{m_1},\ldots,t^{m_n})$, with the parameter $t$ varying in an interval $I$. We show, using constructive arguments, that $K$ admits a lifted semidefinite…

Optimization and Control · Mathematics 2023-03-08 Gennadiy Averkov , Claus Scheiderer

The minimum error discrimination problem for ensembles of linearly independent pure states are known to have an interesting structure; for such a given ensemble the optimal POVM is given by the pretty good measurment of another ensemble…

Quantum Physics · Physics 2014-12-24 Tanmay Singal , Sibasish Ghosh

We consider linear time invariant systems with exogenous stochastic disturbances, and in feedback with structured stochastic uncertainties. This setting encompasses linear systems with both additive and multiplicative noise. Our concern is…

Systems and Control · Computer Science 2020-04-06 Bassam Bamieh , Maurice Filo

A novel optimization method is proposed to minimize a convex function subject to bilinear matrix inequality (BMI) constraints. The key idea is to decompose the bilinear mapping as a difference between two positive semidefinite convex…

Optimization and Control · Mathematics 2011-09-19 Quoc Tran Dinh , Suat Gumussoy , Wim Michiels , Moritz Diehl

We provide convex necessary and sufficient conditions for the robust stability of linear positively dominated systems. In particular we show that the structured singular value is always equal to its convex upper bound for nonnegative…

Optimization and Control · Mathematics 2015-08-21 Marcello Colombino , Roy S. Smith

In this work, we develop a new complexity metric for an important class of low-rank matrix optimization problems in both symmetric and asymmetric cases, where the metric aims to quantify the complexity of the nonconvex optimization…

Optimization and Control · Mathematics 2023-07-24 Haixiang Zhang , Baturalp Yalcin , Javad Lavaei , Somayeh Sojoudi

Matrix regularity is a key to various problems in applied mathematics. The sufficient conditions, used for checking regularity of interval parametric matrices, usually fail in case of large parameter intervals. We present necessary and…

Numerical Analysis · Mathematics 2021-06-29 Evgenija D. Popova

In this paper, we address the problem of computing the maximal admissible robust positive invariant (MARPI) set for discrete-time linear time-varying systems with parametric uncertainties and additive disturbances. The system state and…

Optimization and Control · Mathematics 2024-06-26 Anchita Dey , Shubhendu Bhasin

Let $W_{k,n}^{i}(m)$ denote a matrix with rows and columns indexed by the $k$-subsets and $n$-subsets, respectively, of an $m$-element set. The row $S$, column $T$ entry of $W_{k,n}^{i}(m)$ is $1$ if $|S \cap T| = i$, and is $0$ otherwise.…

Combinatorics · Mathematics 2023-05-09 Joshua E. Ducey , Colby J. Sherwood

Optimal physical layer multicasting (PLM) is an NP-hard problem that for simplicity has been studied under idealistic assumptions, e.g., availability of perfect channel state information (CSI), both at the base station (BS) and at the user…

Information Theory · Computer Science 2017-09-25 Meysam Sadeghi , Emil Björnson , Erik G. Larsson , Chau Yuen , Thomas L. Marzetta

We study convexity of image of a general multidimensional quadratic map. We split the full image into two parts by an appropriate hyperplane such that one part is compact, and formulate a sufficient condition for convexity of the compact…

Optimization and Control · Mathematics 2018-03-23 Anatoly Dymarsky

Mixed-integer convex representable (MICP-R) sets are those sets that can be represented exactly through a mixed-integer convex programming formulation. Following up on recent work by Lubin et al. (2017, 2020) we investigate structural…

Optimization and Control · Mathematics 2021-03-08 Ilias Zadik , Miles Lubin , Juan Pablo Vielma

Stability analysis of discrete-time switched systems under minimum dwell-time is studied using a new type of LMI conditions. These conditions are convex in the matrices of the system and shown to be equivalent to the nonconvex conditions…

Optimization and Control · Mathematics 2013-11-07 Corentin Briat

We study a class of polynomial optimization problems with a robust polynomial matrix inequality (PMI) constraint where the uncertainty set itself is defined also by a PMI. These can be viewed as matrix generalizations of semi-infinite…

Optimization and Control · Mathematics 2024-10-10 Feng Guo , Jie Wang

Parametric linear systems are linear systems of equations in which some symbolic parameters, that is, symbols that are not considered to be candidates for elimination or solution in the course of analyzing the problem, appear in the…

Rings and Algebras · Mathematics 2025-09-01 Robert M. Corless , Mark Giesbrecht , Leili Rafiee Sevyeri , B. David Saunders

We consider the problem of robust matrix completion, which aims to recover a low rank matrix $L_*$ and a sparse matrix $S_*$ from incomplete observations of their sum $M=L_*+S_*\in\mathbb{R}^{m\times n}$. Algorithmically, the robust matrix…

Machine Learning · Statistics 2020-03-25 Yunfeng Cai , Ping Li

Very recently Richter and Rogers proved that any convex geometry can be represented by a family of convex polygons in the plane. We shall generalize their construction and obtain a wide variety of convex shapes for representing convex…

Combinatorics · Mathematics 2017-01-13 J. Kincses