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The classical Kantorovich-Rubinstein duality theorem establishes a significant connection between Monge optimal transport and maximization of a linear form on the set of 1-Lipschitz functions. This result has been widely used in various…

Optimization and Control · Mathematics 2025-11-04 Karol Bołbotowski , Guy Bouchitté

Consider a planar graph $G=(V,E)$ with polynomially bounded edge weight function $w:E\to [0, poly(n)]$. The main results of this paper are NC algorithms for the following problems: - minimum weight perfect matching in $G$, - maximum…

Data Structures and Algorithms · Computer Science 2018-04-20 Piotr Sankowski

In this note, we study an optimal transportation problem arising in density functional theory. We derive an upper bound on the semi-classical Hohenberg-Kohn functional derived by Cotar, Friesecke and Kl\"{u}ppelberg (2012) which can be…

Optimization and Control · Mathematics 2015-06-12 Brendan Pass

We address the problem of producing a lower bound for the mean of a discrete probability distribution, with known support over a finite set of real numbers, from an iid sample of that distribution. Up to a constant, this is equivalent to…

Statistics Theory · Mathematics 2025-02-25 Erik Learned-Miller

We study the problem of discrete geometric packing. Here, given weighted regions (say in the plane) and points (with capacities), one has to pick a maximum weight subset of the regions such that no point is covered more than its capacity.…

Computational Geometry · Computer Science 2011-12-01 Alina Ene , Sariel Har-Peled , Benjamin Raichel

We consider the problem of optimal approximation of a target measure by an atomic measure with $N$ atoms, in branched optimal transport distance. This is a new branched transport version of optimal quantization problems. New difficulties…

Optimization and Control · Mathematics 2025-04-01 Paul Pegon , Mircea Petrache

Kiefer and Wolfowitz [Z. Wahrsch. Verw. Gebiete 34 (1976) 73--85] showed that if $F$ is a strictly curved concave distribution function (corresponding to a strictly monotone density $f$), then the Maximum Likelihood Estimator $\hat{F}_n$,…

Statistics Theory · Mathematics 2007-10-10 Fadoua Balabdaoui , Jon A. Wellner

We introduce a new technique for reducing the dimension of the ambient space of low-degree polynomials in the Gaussian space while preserving their relative correlation structure, analogous to the Johnson-Lindenstrauss lemma. As…

Computational Complexity · Computer Science 2017-08-15 Badih Ghazi , Pritish Kamath , Prasad Raghavendra

In this paper an iterated function system on the space of distribution functions is built. The inverse problem is introduced and studied by convex optimization problems. Some applications of this method to approximation of distribution…

Statistics Theory · Mathematics 2007-06-13 Stefano M. Iacus , Davide La Torre

Approximating a convex function by a polyhedral function that has a limited number of facets is a fundamental problem with applications in various fields, from mitigating the curse of dimensionality in optimal control to bi-level…

Optimization and Control · Mathematics 2025-09-05 Abdellah Bulaich Mehamdi , Wim van Ackooij , Luce Brotcorne , Stéphane Gaubert , Quentin Jacquet

To remedy the drawbacks of full-mass or fixed-mass constraints in classical optimal transport, we propose adaptive optimal transport which is distinctive from the classical optimal transport in its ability of adaptive-mass preserving. It…

Machine Learning · Computer Science 2025-03-10 Pei Yang , Qi Tan , Guihua Wen

Robust and distributionally robust optimization are modeling paradigms for decision-making under uncertainty where the uncertain parameters are only known to reside in an uncertainty set or are governed by any probability distribution from…

Optimization and Control · Mathematics 2023-07-21 Jianzhe Zhen , Daniel Kuhn , Wolfram Wiesemann

Weighted least squares polynomial approximation uses random samples to determine projections of functions onto spaces of polynomials. It has been shown that, using an optimal distribution of sample locations, the number of samples required…

Numerical Analysis · Mathematics 2017-10-10 Abdul-Lateef Haji-Ali , Fabio Nobile , Raúl Tempone , Sören Wolfers

Motivated by economic dispatch and linearly-constrained resource allocation problems, this paper proposes a novel Distributed Approx-Newton algorithm that approximates the standard Newton optimization method. A main property of this…

Numerical Analysis · Computer Science 2017-03-24 Tor Anderson , Chin-Yao Chang , Sonia Martinez

We analyze Kumar's recent quadratic algebraic branching program size lower bound proof method (CCC 2017) for the power sum polynomial. We present a refinement of this method that gives better bounds in some cases. The lower bound relies on…

Computational Complexity · Computer Science 2022-12-27 Fulvio Gesmundo , Purnata Ghosal , Christian Ikenmeyer , Vladimir Lysikov

This survey synthesizes the current state of the art on the regularity theory for solutions to the optimal partition problem. Namely, we consider non-negative, vector-valued Sobolev functions whose components have mutually disjoint support,…

Analysis of PDEs · Mathematics 2025-10-10 Roberto Ognibene , Bozhidar Velichkov

Bounds on the log partition function are important in a variety of contexts, including approximate inference, model fitting, decision theory, and large deviations analysis. We introduce a new class of upper bounds on the log partition…

Machine Learning · Computer Science 2013-01-07 Martin Wainwright , Tommi S. Jaakkola , Alan Willsky

For a family of weight functions invariant under a finite reflection group, the boundedness of a maximal function on the unit sphere is established and used to prove a multiplier theorem for the orthogonal expansions with respect to the…

Classical Analysis and ODEs · Mathematics 2007-05-23 Feng Dai , Yuan Xu

We establish a good lambda inequality relating to the distribution function of Riesz potential and fractional maximal function on $\left(\mathbb{R}^n, d\mu\right)$ where $\mu$ is a positive Radon measure which doesn't necessarily satisfy a…

Functional Analysis · Mathematics 2021-12-21 Dr Mukta Bhandari

We study boundedness, optimality and attainability of Trudinger-Moser type maximization problems in the radial and the subcritical homogeneous Sobolev spaces $\dot{W}^{1,p}_{0, \text{rad}}(B_R^N)\,(p<N)$. Our results give a revision of an…

Analysis of PDEs · Mathematics 2024-09-12 Masahiro Ikeda , Megumi Sano , Koichi Taniguchi