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We develop a new technique for proving distribution testing lower bounds for properties defined by inequalities involving the bin probabilities of the distribution in question. Using this technique we obtain new lower bounds for…

Machine Learning · Computer Science 2023-08-02 Yuqian Cheng , Daniel M. Kane , Zhicheng Zheng

We derive a new estimate of the size of finite sets of points in metric spaces with few distances. The following applications are considered: (1) we improve the Ray-Chaudhuri--Wilson bound of the size of uniform intersecting families of…

Combinatorics · Mathematics 2011-04-29 Alexander Barg , Oleg R. Musin

Maximum entropy models are increasingly being used to describe the collective activity of neural populations with measured mean neural activities and pairwise correlations, but the full space of probability distributions consistent with…

Biological Physics · Physics 2017-08-22 Badr F. Albanna , Christopher Hillar , Jascha Sohl-Dickstein , Michael R. DeWeese

We prove a lower bound for the modulus of the amplitude for a two-body process at large scattering angle. This is based on the interplay of the analyticity of the amplitude and the positivity properties of its absorptive part. The…

High Energy Physics - Theory · Physics 2019-07-03 Henri Epstein , André Martin

This article derives lower bounds on the supremal (strict) p-negative type of finite metric spaces using purely elementary techniques. The bounds depend only on the cardinality and the (scaled) diameter of the underlying finite metric…

Functional Analysis · Mathematics 2008-07-18 Anthony Weston

The canonical dimension is an invariant attached to admissible representations of p-adic reductive groups, which has only received significant attention in the case of mod-p representations. In the case of complex representations, the…

Representation Theory · Mathematics 2025-09-30 Mick Gielen

We give an explicit upper bound for the algebraic degree and an explicit lower bound for the absolute value of the minimum of a polynomial function on a compact connected component of a basic closed semialgebraic set when this minimum is…

Algebraic Geometry · Mathematics 2011-12-05 Gabriela Jeronimo , Daniel Perrucci , Elias Tsigaridas

Upper bounds are given for the weight distribution of binary weakly self-dual codes. To get these new bounds, we introduce a novel method of utilizing unitary operations on Hilbert spaces. This method is motivated by recent progress on…

Combinatorics · Mathematics 2007-07-16 Vwani P. Roychowdhury , Farrokh Vatan

We consider the volume of the largest axis-parallel box in the $d$-dimensional torus that contains no point of a given point set $\mathcal{P}_n$ with $n$ elements. We prove that, for all natural numbers $d, n$ and every point set…

Computational Complexity · Computer Science 2019-08-15 Mario Ullrich

We imagine an experiment on an unknown quantum mechanical system in which the system is prepared in various ways and a range of measurements are performed. For each measurement M and preparation rho the experimenter can determine, given…

Quantum Physics · Physics 2009-01-20 Stephanie Wehner , Matthias Christandl , Andrew C. Doherty

Families of boxes in $\mathbb R^d$ are considered. In the paper an upper bound on the size of a minimum transversal in terms of the space dimension and the independence number of the given family was improved.

Combinatorics · Mathematics 2008-10-21 Arseny Akopyan

In this paper, we prove that some renowned lower bounds in discrepancy theory admit a discrete analogue. Namely, we prove that the lower bound of the discrepancy for corners in the unit cube due to Roth holds true also for a suitable finite…

Classical Analysis and ODEs · Mathematics 2025-03-06 Luca Brandolini , Bianca Gariboldi , Giacomo Gigante , Alessandro Monguzzi

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

We introduce a simple method for proving lower bounds for the size of the smallest percolating set in a certain graph bootstrap process. We apply this method to determine the sizes of the smallest percolating sets in multidimensional tori…

Combinatorics · Mathematics 2021-05-11 Lianna Hambardzumyan , Hamed Hatami , Yingjie Qian

The paper explores a new extremality model involving collections of arbitrary families of sets. We demonstrate its applicability to set-valued optimization problems with general preferences, weakening the assumptions of the known results…

Optimization and Control · Mathematics 2025-06-23 Nguyen Duy Cuong , Alexander Y. Kruger , Nguyen Hieu Thao

We give an attempt to build a classification of planar integral point sets. For two obtained classes, we provide general constructions of upper bounds for minimal diameter of integral point sets in higher dimensions of certain cardinality.…

Combinatorics · Mathematics 2021-11-23 N. N. Avdeev , R. E. Zvolinsky , E. A. Momot

We investigate the box dimensions of compact sets in $\mathbb{R}^2$ that contain a unit distance in every direction (such sets may have zero Hausdorff dimension). Among other results, we show that the lower box dimension must be at least…

Classical Analysis and ODEs · Mathematics 2021-07-05 Pablo Shmerkin , Han Yu

We show that the minimum distance projection in the L1-norm from an interior point onto the boundary of a convex set is achieved by a single, unidimensional projection. Application of this characterization when the convex set is a…

Optimization and Control · Mathematics 2007-05-23 Hans J. H. Tuenter

In this paper we present a new bound obtained with the probabilistic method for the solution of the Set Covering problem with unit costs. The bound is valid for problems of fixed dimension, thus extending previous similar asymptotic…

Combinatorics · Mathematics 2014-07-18 Giovanni Felici , Sokol Ndreca , Aldo Procacci , Benedetto Scoppola

We present a new method to propagate lower bounds on conditional probability distributions in conventional Bayesian networks. Our method guarantees to provide outer approximations of the exact lower bounds. A key advantage is that we can…

Artificial Intelligence · Computer Science 2012-05-14 Daniel Andrade , Bernhard Sick