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Recent advances in statistics introduced versions of the central limit theorem for high-dimensional vectors, allowing for the construction of confidence regions for high-dimensional parameters. In this note, $s$-sparsely convex…

Statistics Theory · Mathematics 2021-05-20 Sven Klaassen

This thesis reviews numerical optimization methods with machine learning problems in mind. Since machine learning models are highly parametrized, we focus on methods suited for high dimensional optimization. We build intuition on quadratic…

Optimization and Control · Mathematics 2022-01-03 Felix Benning

There are already quite a few tools for solving the Satisfiability Modulo Theories (SMT) problems. In this paper, we present \texttt{VolCE}, a tool for counting the solutions of SMT constraints, or in other words, for computing the volume…

Artificial Intelligence · Computer Science 2015-07-02 Cunjing Ge , Feifei Ma , Jian Zhang

The purpose of this note is to present several aspects of concentration phenomena in high dimensional geometry. At the heart of the study is a geometric analysis point of view coming from the theory of high dimensional convex bodies. The…

Functional Analysis · Mathematics 2013-10-07 Olivier Guédon

Given a many-body system, we define a quantity, the Codification Volume of an operator algebra, which measures the size of the subspace with whom a given algebra is correlated. We explicitly calculate it for some limit cases, including…

Quantum Physics · Physics 2014-10-24 Javier M. Magan , Simone Paganelli

Given a prediction task, understanding when one can and cannot design a consistent convex surrogate loss, particularly a low-dimensional one, is an important and active area of machine learning research. The prediction task may be given as…

Machine Learning · Computer Science 2021-02-17 Jessie Finocchiaro , Rafael Frongillo , Bo Waggoner

Using combinatorial methods, we derive several formulas for the volume of convex bodies obtained by intersecting a unit hypercube with a halfspace, or with a hyperplane of codimension 1, or with a flat defined by two parallel hyperplanes.…

Metric Geometry · Mathematics 2008-02-12 Jean-Luc Marichal , Michael J. Mossinghoff

We consider the moments of the volume of the symmetric convex hull of independent random points in an $n$-dimensional symmetric convex body. We calculate explicitly the second and fourth moments for $n$ points when the given body is $B_q^n$…

Metric Geometry · Mathematics 2007-05-23 Mark W. Meckes

We compute the volume of the body enclosed by the $n$-dimensional Lam\'e curve defined by $\sum_{i=1}^nx_i^b= E$.

Statistical Mechanics · Physics 2009-12-04 Raul Toral

Let $S$ be a set of $n$ points in $\mathbb{R}^d$. A Steiner convex partition is a tiling of ${\rm conv}(S)$ with empty convex bodies. For every integer $d$, we show that $S$ admits a Steiner convex partition with at most $\lceil…

Computational Geometry · Computer Science 2014-02-04 Adrian Dumitrescu , Sariel Har-Peled , Csaba D. Tóth

Volume is a natural geometric measure for comparing polyhedral relaxations of non-convex sets. Speakman and Lee gave volume formulae for comparing relaxations of trilinear monomials, quantifying the strength of various natural relaxations.…

Optimization and Control · Mathematics 2018-10-18 Emily Speakman , Han Yu , Jon Lee

The intrinsic volumes of a convex body are fundamental invariants that capture information about the average volume of the projection of the convex body onto a random subspace of fixed dimension. The intrinsic volumes also play a central…

Metric Geometry · Mathematics 2022-08-31 Martin Lotz , Joel A. Tropp

We define a stochastic model of a two-sided limit order book in terms of its key quantities \textit{best bid [ask] price} and the \textit{standing buy [sell] volume density}. For a simple scaling of the discreteness parameters, that keeps…

Mathematical Finance · Quantitative Finance 2015-01-06 Ulrich Horst , Michael Paulsen

We investigate the information complexity of mixed-integer convex optimization under different types of oracles. We establish new lower bounds for the standard first-order oracle, improving upon the previous best known lower bound. This…

Optimization and Control · Mathematics 2023-08-23 Amitabh Basu , Hongyi Jiang , Phillip Kerger , Marco Molinaro

By Andreev theorem acute-angled polyhedra of finite volume in a hyperbolic space $\mathbb H^{3}$ are uniquely determined by combinatorics of their 1-skeletons and dihedral angles. For a class of compact right-angled polyhedra and a class of…

Geometric Topology · Mathematics 2020-10-22 A. Egorov , A. Vesnin

We perform a fundamental investigation of the complexity of conjunctive query evaluation from the perspective of parameterized complexity. We classify sets of boolean conjunctive queries according to the complexity of this problem. Previous…

Computational Complexity · Computer Science 2013-06-26 Hubie Chen , Moritz Müller

Consider a graph problem that is locally checkable but not locally solvable: given a solution we can check that it is feasible by verifying all constant-radius neighborhoods, but to find a solution each node needs to explore the input graph…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-02-19 Will Rosenbaum , Jukka Suomela

This paper contains a new concept to measure the width and thickness of a convex body in the hyperbolic plane. We compare the known concepts with the new one and prove some results on bodies of constant width, constant diameter and given…

Metric Geometry · Mathematics 2020-12-01 Ákos G. Horváth

The convex hull of N independent random points chosen on the boundary of a simple polytope in R^n is investigated. Asymptotic formulas for the expected number of vertices and facets, and for the expectation of the volume difference are…

Probability · Mathematics 2022-01-11 M. Reitzner , C. Schuett , E. M. Werner

This article gives estimates on covering numbers and diameters of random proportional sections and projections of symmetric quasi-convex bodies in $\mathbb R$. These results were known for the convex case and played an essential role in…

Metric Geometry · Mathematics 2008-02-03 A. E. Litvak , V. D. Milman , A. Pajor