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We derive lower estimates for the approximation of the $d$-dimensional Euclidean ball by polytopes with a fixed number of $k$-dimensional faces, $k\in\{0,1,\ldots,d-1\}$. The metrics considered include the intrinsic volume difference and…

Metric Geometry · Mathematics 2025-10-28 Steven Hoehner , Carsten Schütt , Elisabeth Werner

In this paper we introduce a new family of Bernstein-type exponential polynomials on the hypercube $[0, 1]^d$ and study their approximation properties. Such operators fix a multidimensional version of the exponential function and its…

Classical Analysis and ODEs · Mathematics 2024-05-28 Laura Angeloni , Danilo Costarelli , Chiara Darielli

We derive a computable closed-form upper bound on the Hausdorff distance between a truncated minimal robust positively invariant (mRPI) set and its infinite-horizon limit. The bound depends only on a disturbance-set size measure and an…

Robotics · Computer Science 2026-05-12 Jiaxun Sun , Hengyu Xue , Yuyang Zhao

We consider the online version of the piercing set problem, where geometric objects arrive one by one, and the online algorithm must maintain a valid piercing set for the already arrived objects by making irrevocable decisions. It is easy…

Computational Geometry · Computer Science 2024-07-04 Minati De , Saksham Jain , Sarat Varma Kallepalli , Satyam Singh

In this article, we focus on computing the quantiles of a random variable $f(X)$, where $X$ is a $[0,1]^d$-valued random variable, $d \in \mathbb{N}^{\ast}$, and $f:[0,1]^d\to \mathbb{R}$ is a deterministic Lipschitz function. We are…

Probability · Mathematics 2024-10-30 Yurun Gu , Clément Rey

We develop and analyze a set of new sequential simulation-optimization algorithms for large-scale multi-dimensional discrete optimization via simulation problems with a convexity structure. The "large-scale" notion refers to that the…

Optimization and Control · Mathematics 2022-01-20 Haixiang Zhang , Zeyu Zheng , Javad Lavaei

Consider a non-negative number $t$ and a hyperplane $H$ of $\mathbb{R}^d$ whose distance to the center of the hypercube $[0,1]^d$ is $t$. If $t$ is equal to $0$ and $H$ is orthogonal to a diagonal of $[0,1]^d$, it is known that the…

Metric Geometry · Mathematics 2025-03-05 Lionel Pournin

We present a new algorithm to calculate exact hypervolumes. Given a set of $d$-dimensional points, it computes the hypervolume of the dominated space. Determining this value is an important subroutine of Multiobjective Evolutionary…

Data Structures and Algorithms · Computer Science 2012-11-30 Luís M. S. Russo , Alexandre P. Francisco

Available algorithms for the initialization of volume fractions typically utilize exact functions to model fluid interfaces, or they rely on computationally costly intersections between volume meshes. Here, a new algorithm is proposed that…

Computational Physics · Physics 2024-02-07 Tobias Tolle , Dirk Gründing , Dieter Bothe , Tomislav Marić

Benchmark instances for the unbounded knapsack problem are typically generated according to specific criteria within a given constant range $R$, and these instances can be referred to as the unbounded knapsack problem with bounded…

Data Structures and Algorithms · Computer Science 2024-03-19 Yang Yang

In this paper we study the subset sum problem with real numbers. Starting from the given problem, we formulate a quadratic maximization problem over a polytope which is eventually written as a distance maximization to a fixed point. For…

Optimization and Control · Mathematics 2023-10-09 Marius Costandin

We study the convergence rate of randomly truncated stochastic algorithms, which consist in the truncation of the standard Robbins-Monro procedure on an increasing sequence of compact sets. Such a truncation is often required in practice to…

Probability · Mathematics 2010-04-08 Jérôme Lelong

We study the convergence rate of randomly truncated stochastic algorithms, which consist in the truncation of the standard Robbins-Monro procedure on an increasing sequence of compact sets. Such a truncation is often required in practice to…

Probability · Mathematics 2010-03-23 Jérôme Lelong

Volume of metric balls relates to rate-distortion theory and packing bounds on codes. In this paper, the volume of balls in complex Grassmann manifolds is evaluated for an arbitrary radius. The ball is defined as a set of hyperplanes of a…

Information Theory · Computer Science 2015-08-04 Renaud-Alexandre Pitaval , Lu Wei , Olav Tirkkonen , Jukka Corander

We give an algorithm to compute a one-dimensional shape-constrained function that best fits given data in weighted-$L_{\infty}$ norm. We give a single algorithm that works for a variety of commonly studied shape constraints including…

Data Structures and Algorithms · Computer Science 2019-05-30 David Durfee , Yu Gao , Anup B. Rao , Sebastian Wild

It was recently shown [7, 9] that "properly built" linear and polyhedral estimates nearly attain minimax accuracy bounds in the problem of recovery of unknown signal from noisy observations of linear images of the signal when the signal set…

Optimization and Control · Mathematics 2023-12-25 Yannis Bekri , Anatoli Juditsky , Arkadi Nemirovski

We present a simple phenomenological formula which approximates the hyperbolic volume of a knot using only a single evaluation of its Jones polynomial at a root of unity. The average error is just $2.86$% on the first $1.7$ million knots,…

High Energy Physics - Theory · Physics 2021-06-30 Jessica Craven , Vishnu Jejjala , Arjun Kar

The H\"older continuity of the truncated moment map of a shade function in Euclidean space is established in the vicinity of a principal semi-algebraic set. The proof combines volume bounds of semi-algebraic sets and convex optimization…

Classical Analysis and ODEs · Mathematics 2020-08-14 Mihai Putinar

We propose a decomposition framework for the parallel optimization of the sum of a differentiable {(possibly nonconvex)} function and a nonsmooth (possibly nonseparable), convex one. The latter term is usually employed to enforce structure…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-07-19 Amir Daneshmand , Francisco Facchinei , Vyacheslav Kungurtsev , Gesualdo Scutari

We study the complexity of computing the VC Dimension and Littlestone's Dimension. Given an explicit description of a finite universe and a concept class (a binary matrix whose $(x,C)$-th entry is $1$ iff element $x$ belongs to concept…

Computational Complexity · Computer Science 2017-05-29 Pasin Manurangsi , Aviad Rubinstein
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