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The problem of non-iterative one-shot and non-destructive correction of unavoidable mistakes arises in all Artificial Intelligence applications in the real world. Its solution requires robust separation of samples with errors from samples…

Machine Learning · Computer Science 2017-09-05 A. N. Gorban , I. Y. Tyukin

Given a set $P$ of $n$ points in $\mathbf{R}^d$, and a positive integer $k \leq n$, the $k$-dispersion problem is that of selecting $k$ of the given points so that the minimum inter-point distance among them is maximized (under Euclidean…

Computational Geometry · Computer Science 2025-11-04 Ke Chen , Adrian Dumitrescu

According to Aistleitner and Weimar, there exist two-dimensional (double) infinite matrices whose star-discrepancy $D_N^{*s}$ of the first $N$ rows and $s$ columns, interpreted as $N$ points in $[0,1]^s$, satisfies an inequality of the form…

Number Theory · Mathematics 2026-01-13 Jasmin Fiedler , Michael Gnewuch , Christian Weiß

Point set registration is a key component in many computer vision tasks. The goal of point set registration is to assign correspondences between two sets of points and to recover the transformation that maps one point set to the other.…

Computer Vision and Pattern Recognition · Computer Science 2010-11-09 Andriy Myronenko , Xubo Song

Although globular clusters are generally chemically homogeneous, substantial abundance variations are sometimes seen even among unevolved main sequence stars, especially for the CNO group of elements. Multi-object intermediate-dispersion…

Astrophysics · Physics 2007-05-23 Russell Cannon , Gary Da Costa , John Norris , Laura Stanford , Barry Croke

Motivated by problems in controlled experiments, we study the discrepancy of random matrices with continuous entries where the number of columns $n$ is much larger than the number of rows $m$. Our first result shows that if $\omega(1) = m =…

Discrete Mathematics · Computer Science 2020-11-10 Paxton Turner , Raghu Meka , Philippe Rigollet

In complicated/nonlinear parametric models, it is generally hard to know whether the model parameters are point identified. We provide computationally attractive procedures to construct confidence sets (CSs) for identified sets of full…

Methodology · Statistics 2022-06-06 Xiaohong Chen , Timothy Christensen , Elie Tamer

Statistically sound crystallographic symmetry classifications are obtained with information theory based methods in the presence of approximately Gaussian distributed noise. A set of three synthetic patterns with strong Fedorov type…

Materials Science · Physics 2022-05-03 Peter Moeck

In this paper we design non-uniform bit-wise puncturing distributions for irregular non-binary LDPC (NB-LDPC) codes. The puncturing distributions are optimized by minimizing the decoding threshold of the punctured LDPC code, the threshold…

Information Theory · Computer Science 2010-05-03 Matteo Gorgoglione , Valentin Savin , David Declercq

Given a closed Riemann surface $\Sigma$ equipped with a volume form $\omega$, we construct a natural probability measure on the space $\mathcal{M}_d(\Sigma)$ of degree $d$ branched coverings from $\Sigma$ to the Riemann sphere…

Algebraic Geometry · Mathematics 2020-04-07 Michele Ancona

In this paper, we analyze several critical issues in semi-device independent quantum information processing protocol. In practical experimental realization randomness generation in that scenario is possible only if the efficiency of the…

Quantum Physics · Physics 2015-06-23 Hong-Wei Li , Zhen-Qiang Yin , Marcin Pawlowski , Guang-Can Guo , Zheng-Fu Han

The statistical distribution, when determined from an incomplete set of constraints, is shown to be suitable as host for encrypted information. We design an encoding/decoding scheme to embed such a distribution with hidden information. The…

Statistical Mechanics · Physics 2015-06-25 L. Rebollo-Neira , A Plastino

In terms of statistical fluctuations, stellar population synthesis models are only asymptotically correct in the limit of a large number of stars, where sampling errors become asymptotically small. When dealing with stellar clusters,…

Astrophysics · Physics 2009-12-15 M. Cervino , D. Valls-Gabaud , V. Luridiana , J. M. Mas-Hesse

Delone sets are discrete point sets $X$ in $\mathbb{R}^d$ characterized by parameters $(r,R)$, where (usually) $2r$ is the smallest inter-point distance of $X$, and $R$ is the radius of a largest ``empty ball" that can be inserted into the…

Metric Geometry · Mathematics 2023-06-21 Nikolay Dolbilin , Alexey Garber , Egon Schulte , Marjorie Senechal

Subsets of F_2^n that are eps-biased, meaning that the parity of any set of bits is even or odd with probability eps close to 1/2, are powerful tools for derandomization. A simple randomized construction shows that such sets exist of size…

Computational Complexity · Computer Science 2013-04-19 Cristopher Moore , Alexander Russell

A significant fraction of, and possibly all, stars form in binary or multiple systems. For Solar-mass stars in the Galactic field, the distribution of orbital separations is log-normal over seven orders of magnitude, from $10^{-2} - 10^5$…

Solar and Stellar Astrophysics · Physics 2025-07-23 Mary H. Rawcliffe , Nathan Griffiths-Janvier , Richard J. Parker

We consider the problem of learning a discrete distribution in the presence of an $\epsilon$ fraction of malicious data sources. Specifically, we consider the setting where there is some underlying distribution, $p$, and each data source…

Machine Learning · Computer Science 2017-11-23 Mingda Qiao , Gregory Valiant

Harnessing quantum processes is an efficient method to generate truly indeterministic random numbers, which are of fundamental importance for cryptographic protocols, security applications or Monte-Carlo simulations. Recently, quantum…

Quantum Physics · Physics 2019-11-14 Johannes Thewes , Carolin Lüders , Marc Aßmann

Out-of-distribution (OOD) generalization has attracted increasing research attention in recent years, due to its promising experimental results in real-world applications. In this paper,we study the confidence set prediction problem in the…

Machine Learning · Computer Science 2024-04-01 Xin Zou , Weiwei Liu

A non-redundant integer cone generator (NICG) of dimension $d$ is a set $S$ of vectors from $\{0,1\}^d$ whose vector sum cannot be generated as a positive integer linear combination of a proper subset of $S$. The largest possible…

Logic in Computer Science · Computer Science 2019-03-21 Slobodan Mitrović , Ruzica Piskac , Viktor Kunčak