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A tuple (Z_1,...,Z_p) of matrices of size r is said to be a commuting extension of a tuple (A_1,...,A_p) of matrices of size n <r if the Z_i pairwise commute and each A_i sits in the upper left corner of a block decomposition of Z_i. This…

Data Structures and Algorithms · Computer Science 2024-01-03 Pascal Koiran

We present a general technique, based on parametric search with some twist, for solving a variety of optimization problems on a set of semi-algebraic geometric objects of constant complexity. The common feature of these problems is that…

Computational Geometry · Computer Science 2022-07-15 Matthew J. Katz , Micha Sharir

For an upper bidiagonal matrix $B$ where all the diagonal and the upper subdiagonal entries are positive, two subtraction-free formulae for computation of the traces $J_{M} ( B ) = \textrm{Tr} ( ( B^{\top} B )^{- M} ) = \textrm{Tr} ( ( B…

Numerical Analysis · Mathematics 2014-11-14 Takumi Yamashita

Discrete optimal transportation problems arise in various contexts in engineering, the sciences and the social sciences. Often the underlying cost criterion is unknown, or only partly known, and the observed optimal solutions are corrupted…

Optimization and Control · Mathematics 2019-05-13 Andrew M. Stuart , Marie-Therese Wolfram

Given two probability measures $\mu$ and $\nu$ in "convex order" on $\R^d$, we study the profile of one-step martingale plans $\pi$ on $\R^d\times \R^d$ that optimize the expected value of the modulus of their increment among all…

Analysis of PDEs · Mathematics 2016-04-07 Nassif Ghoussoub , Young-Heon Kim , Tongseok Lim

In this paper, we study dynamical optimal transport on a connected graph from the perspective of the Benamou-Brenier formulation, where densities are assigned to vertices and velocities to edges. However, directly using Newton's method on…

Numerical Analysis · Mathematics 2026-05-11 Qujiangxue Chen , Jianbo Cui , Luca Dieci , Haomin Zhou

In this paper, we introduce a powerful technique based on Leave-one-out analysis to the study of low-rank matrix completion problems. Using this technique, we develop a general approach for obtaining fine-grained, entrywise bounds for…

Machine Learning · Statistics 2020-06-18 Lijun Ding , Yudong Chen

The accurate solution of some of the main problems in numerical linear algebra (linear system solving, eigenvalue computation, singular value computation and the least squares problem) for a totally positive Bernstein-Vandermonde matrix is…

Numerical Analysis · Mathematics 2008-12-17 Ana Marco , Jose-Javier Martinez

We study the Schr\"odinger-Bass problem, a one-parameter family of semimartingale optimal transport problems indexed by $\beta>0$, whose limiting regimes interpolate between the classical Schr\"odinger bridge, the Brenier-Strassen problem,…

Probability · Mathematics 2026-04-03 Manuel Hasenbichler , Gudmund Pammer , Stefan Thonhauser

The uniform distribution on matrices with specified row and column sums is often a natural choice of null model when testing for structure in two-way tables (binary or nonnegative integer). Due to the difficulty of sampling from this…

Computation · Statistics 2013-08-14 Jeffrey W. Miller , Matthew T. Harrison

In this work, we study a variant of nonnegative matrix factorization where we wish to find a symmetric factorization of a given input matrix into a sparse, Boolean matrix. Formally speaking, given $\mathbf{M}\in\mathbb{Z}^{m\times m}$, we…

Machine Learning · Computer Science 2022-01-14 Sitan Chen , Zhao Song , Runzhou Tao , Ruizhe Zhang

We study optimal transport plans from $m$ equally weighted points (with weights $1/m$) to $n$ equally weighted points (with weights $1/n$). The Birkhoff-von Neumann Theorem implies that if $m=n$, then the optimal transport plan can be…

Optimization and Control · Mathematics 2023-12-08 Alexander Bruce Johnson , Stefan Steinerberger

Inspired by the matching of supply to demand in logistical problems, the optimal transport (or Monge--Kantorovich) problem involves the matching of probability distributions defined over a geometric domain such as a surface or manifold. In…

Optimization and Control · Mathematics 2018-05-02 Justin Solomon

A $d$-dimensional matrix is called \emph{$1$-polystochastic} if it is non-negative and the sum over each line equals~$1$. Such a matrix that has a single $1$ in each line and zeros elsewhere is called a \emph{$1$-permutation} matrix. A…

Combinatorics · Mathematics 2020-04-30 Billy Child , Ian M. Wanless

The Brunn-Minkowski inequality, applicable to bounded measurable sets $A$ and $B$ in $\mathbb{R}^d$, states that $|A+B|^{1/d} \geq |A|^{1/d}+|B|^{1/d}$. Equality is achieved if and only if $A$ and $B$ are convex and homothetic sets in…

Analysis of PDEs · Mathematics 2024-07-16 Alessio Figalli , Peter van Hintum , Marius Tiba

We show that the series of all walks between any two vertices of any (possibly weighted) directed graph $\mathcal{G}$ is given by a universal continued fraction of finite depth and breadth involving the simple paths and simple cycles of…

Discrete Mathematics · Computer Science 2015-01-12 P. -L. Giscard , S. J. Thwaite , D. Jaksch

A transportation polytope consists of all multidimensional arrays or tables of non-negative real numbers that satisfy certain sum conditions on subsets of the entries. They arise naturally in optimization and statistics, and also have…

Combinatorics · Mathematics 2013-07-02 Jesús A. De Loera , Edward D. Kim

Sliced Optimal Transport (SOT) is a rapidly developing branch of optimal transport (OT) that exploits the tractability of one-dimensional OT problems. By combining tools from OT, integral geometry, and computational statistics, SOT enables…

Machine Learning · Statistics 2025-10-15 Khai Nguyen

The iterative method of Sinkhorn allows, starting from an arbitrary real matrix with non-negative entries, to find a so-called 'scaled matrix' which is doubly stochastic, i.e. a matrix with all entries in the interval (0, 1) and with all…

Mathematical Physics · Physics 2015-02-09 Alexis De Vos , Stijn De Baerdemacker

It was recently shown that under smoothness conditions, the squared Wasserstein distance between two distributions could be efficiently computed with appealing statistical error upper bounds. However, rather than the distance itself, the…

Machine Learning · Statistics 2021-12-30 Boris Muzellec , Adrien Vacher , Francis Bach , François-Xavier Vialard , Alessandro Rudi