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Graphical models have become a very popular tool for representing dependencies within a large set of variables and are key for representing causal structures. We provide results for uniform inference on high-dimensional graphical models…

Methodology · Statistics 2018-12-04 Sven Klaassen , Jannis Kück , Martin Spindler , Victor Chernozhukov

The classification of individual traffic participants is a complex task, especially for challenging scenarios with multiple road users or under bad weather conditions. Radar sensors provide an - with respect to well established camera…

Machine Learning · Computer Science 2019-05-28 Nicolas Scheiner , Nils Appenrodt , Jürgen Dickmann , Bernhard Sick

We consider the problem of determining the expected dimension of the star product of two uniformly random linear codes that are not necessarily of the same dimension. We achieve this by establishing a correspondence between the star product…

Information Theory · Computer Science 2025-11-24 Johan V. Dinesen , Ragnar Freij-Hollanti , Camilla Hollanti , Benjamin Jany , Alberto Ravagnani

Tabular structures are used to present crucial information in a structured and crisp manner. Detection of such regions is of great importance for proper understanding of a document. Tabular structures can be of various layouts and types.…

Computer Vision and Pattern Recognition · Computer Science 2020-08-28 Soumyadeep Dey , Jayanta Mukhopadhyay , Shamik Sural

Slope difference distribution (SDD) is computed for the one-dimensional curve. It is not only robust to calculate the partitioning point to separate the curve logically, but also robust to calculate the clustering center of each part of the…

Computer Vision and Pattern Recognition · Computer Science 2020-09-04 Zhenzhou Wang

Since the label collecting is prohibitive and time-consuming, unsupervised methods are preferred in applications such as fraud detection. Meanwhile, such applications usually require modeling the intrinsic clusters in high-dimensional data,…

Machine Learning · Computer Science 2020-12-16 Han Zhang , Wenhao Zheng , Charley Chen , Kevin Gao , Yao Hu , Ling Huang , Wei Xu

Current practice in parameter space exploration in euclidean space is dominated by randomized sampling or design of experiment methods. The biggest issue with these methods is not keeping track of what part of parameter space has been…

Machine Learning · Computer Science 2023-03-16 Avinash Kumar , Anish Kumar , Sumit Sharma , Surjeet Singh , Kumar Vardhan

A generalization of the random geometric graph (RGG) model is proposed by considering a set of points uniformly and independently distributed on a rectangle of unit area instead of on a unit square [0,1]^2. The topological properties of the…

Physics and Society · Physics 2015-05-20 Ernesto Estrada , Matthew Sheerin

The standard method of transforming a continuous distribution on the line to the uniform distribution on the unit interval is the probability integral transform. Analogous transforms exist on compact Riemannian manifolds, in that, for each…

Statistics Theory · Mathematics 2018-11-13 P. E. Jupp , A. Kume

Multidimensional record patterns are random sets of lattice points defined by means of a recursive stochastic construction. The patterns thus generated owe their richness to the fact that the construction is not based on a total order,…

Statistical Mechanics · Physics 2020-06-11 P. L. Krapivsky , J. M. Luck

It is widely believed that range resolution, the ability to distinguish between two closely situated targets, depends inversely on the bandwidth of the transmitted radar signal. Here we demonstrate a different type of ranging system, which…

Signal Processing · Electrical Eng. & Systems 2021-06-30 Rony Komissarov , Vitali Kozlov , Dmitry Filonov , Pavel Ginzburg

We propose a computationally efficient method to construct nonparametric, heteroscedastic prediction bands for uncertainty quantification, with or without any user-specified predictive model. Our approach provides an alternative to the…

Machine Learning · Statistics 2023-01-18 Tengyuan Liang

Computer experiments refer to the study of real systems using complex simulation models. They have been widely used as alternatives to physical experiments. Design and analysis of computer experiments have attracted great attention in past…

Methodology · Statistics 2025-04-29 Anita Shahrokhian , Xinwei Deng , C. Devon Lin

Verifying uniform conditions over continuous spaces through random sampling is fundamental in machine learning and control theory, yet classical coverage analyses often yield conservative bounds, particularly at small failure probabilities.…

Machine Learning · Computer Science 2025-12-15 Lyu Yuhuan

Simulation-based inference methods that feature correct conditional coverage of confidence sets based on observations that have been compressed to a scalar test statistic require accurate modeling of either the p-value function or the…

Machine Learning · Statistics 2025-08-18 Ali Al Kadhim , Harrison B. Prosper

In radar systems, unimodular (or constant-modulus) waveform design plays an important role in achieving better clutter/interference rejection, as well as a more accurate estimation of the target parameters. The design of such sequences has…

Signal Processing · Electrical Eng. & Systems 2022-08-10 Shahin Khobahi , Arindam Bose , Mojtaba Soltanalian

A numerical approach to design unitary constellation for any dimension and any transmission rate under non-coherent Rayleigh flat fading channel.

Optimization and Control · Mathematics 2025-10-20 Guangyue Han , Joachim Rosenthal

The sum-rank metric arises as an algebraic approach for coding in MIMO block-fading channels and multishot network coding. Codes designed in the sum-rank metric have raised interest in applications such as streaming codes, robust coded…

Information Theory · Computer Science 2023-03-22 Cornelia Ott , Hedongliang Liu , Antonia Wachter-Zeh

A density matrix describes the statistical state of a quantum system. It is a powerful formalism to represent both the quantum and classical uncertainty of quantum systems and to express different statistical operations such as measurement,…

Machine Learning · Computer Science 2024-05-01 Fabio A. González , Alejandro Gallego , Santiago Toledo-Cortés , Vladimir Vargas-Calderón

Radar is a key component of the suite of perception sensors used for safe and reliable navigation of autonomous vehicles. Its unique capabilities include high-resolution velocity imaging, detection of agents in occlusion and over long…

Computer Vision and Pattern Recognition · Computer Science 2023-09-29 Arvind Srivastav , Soumyajit Mandal