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We are delighted to organize and host the second edition of the biennial Summer School on Random Matrices at the University of Michigan during June 18--29, 2018.We thank the Michigan Center for Applie...
Rajendra Bhatia has made remarkable contributions to Mathematics research and teaching, and to growth of Mathematics in India. He has been honored with various awards including the Medal for Young Sci...
Matrix and tensor factorizations have a long history in machine learning. Being able to recover latent factors in the data and flexible enough to accommodate a large set of constraints and regularizat...
We investigate the use of polynomial matrices to give efficient presentations of nonnegative matrices exhibiting prescribed spectral and algebraic behavior.
Let G be a finite group. We classify G-equivariant flow equivalence of nontrivial irreducible shifts of finite type interms of (i) elementary equivalence of matrices over ZG and (ii) the conjugacy cla...
Traffic matrices are required inputs for many IP network management tasks: for instance, capacity planning, traffic engineering and network reliability analysis. However, it is diffi...
We interpret non-negative matrix factorization geometrically, as the problem of finding a simplicial cone which contains a cloud of data points and which is contained in the positive orthant.
Analyzing work functions and the IO variables they need is an important component of designing and evaluating complex systems. We develop a biclustering method for jointly grouping work functions a...
Given a matrix M of low-rank, we consider the problem of reconstructing it from noisy observations of a small, random subset of its entries. The problem arises in a variety of applications, from colla...
Let M be a random nα × n matrix of rank r ≪ n, and assume that a uniformly random subset E of its entries is observed. We describe an efficient algorithm that reconstructs M from |E| = O(r ...
Inspired by recent work of Byers we establish a simple connection between the singular values of a transfer matrix evaluated along the imaginary axis and the imaginary eigenvalues of a related Hamilto...
The ith singular value of a transfer matrix need not be a differentiable function of frequency where its multiplicity is greater than one. We show that near a local maximum, however, the largest singu...
A wide variety of problems in system and control theory can be formulated (or reformulated) as convex optimization problems involving linear matrix inequalities, that is, constraints requiring an affi...
A wide variety of problems in systems and control theory can be cast or recast as convex problems that involve linear matrix inequalities (LMIs). For a few very special cases there are “analytical sol...
The purpose of this paper is to give a historical view of Linear Matrix Inequalities in control and system theory. Not surprisingly, it appears that LMIs have been involved in some of the major events...

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