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The m-out-of-n bootstrap, originally proposed by Bickel, Gotze, and Zwet (1992), approximates the distribution of a statistic by repeatedly drawing m subsamples (with m much smaller than n) without replacement from an original sample of…

Machine Learning · Computer Science 2025-10-27 Imon Banerjee , Sayak Chakrabarty

Jackknife empirical likelihood (JEL) is an effective modified version of empirical likelihood method (EL). Through the construction of the jackknife pseudo-values, JEL overcomes the computational difficulty of EL method when its constraints…

Methodology · Statistics 2016-03-15 Ying-Ju Chen , Wei Ning

We have modeled the employment/population ratio in the largest developed countries. Our results show that the evolution of the employment rate since 1970 can be predicted with a high accuracy by a linear dependence on the logarithm of real…

General Finance · Quantitative Finance 2011-09-21 Ivan Kitov , Oleg Kitov

A large driver of the complexity of graph learning is the interplay between structure and features. When analyzing the expressivity of graph neural networks, however, existing approaches ignore features in favor of structure, making it…

Machine Learning · Computer Science 2026-03-04 Martin Carrasco , Olga Zaghen , Kavir Sumaraj , Erik Bekkers , Bastian Rieck

This paper analyzes the ergodic hypothesis in the context of Boltzmann's late work in statistical mechanics, where Boltzmann lays the foundations for what is today known as the typicality account. I argue that, based on the concepts of…

Statistical Mechanics · Physics 2023-07-13 Paula Reichert

You may have seen the words "topological recursion" mentioned in papers on matrix models, Hurwitz theory, Gromov-Witten theory, topological string theory, knot theory, topological field theory, JT gravity, cohomological field theory, free…

Mathematical Physics · Physics 2026-02-18 Vincent Bouchard

The conventional economic approaches explore very little about the dynamics of the economic systems. Since such systems consist of a large number of agents interacting nonlinearly they exhibit the properties of a complex system. Therefore…

General Physics · Physics 2012-04-01 B. G. Sharma , Sadhana Agrawal , Malti Sharma , D. P. Bisen , Ravi Sharma

Leo A. Goodman was born on August 7, 1928 in New York City. He received his A.B. degree, summa cum laude, in 1948 from Syracuse University, majoring in mathematics and sociology. He went on to pursue graduate studies in mathematics, with an…

Methodology · Statistics 2010-10-05 Mark P. Becker

The ASTROMOVES project studies the career moves and the career decision-making of astrophysicists. The astrophysicists participating have to have made at least two career moves after receiving their doctorates, which is usually between 4…

Instrumentation and Methods for Astrophysics · Physics 2021-12-07 Jarita Holbrook

The Large Hadron Collider, LHC, though meant for discovery, will provide enough data from early phase to also perform various studies of Standard Model processes in as yet unexplored kinematic regions. Precision measurements of the…

High Energy Physics - Experiment · Physics 2008-09-10 Kajari Mazumdar

We generalize the notion of analytic/Borel equivalence relations, orbit equivalence relations, and Borel reductions between them to their continuous and quantitative counterparts: analytic/Borel pseudometrics, orbit pseudometrics, and Borel…

Functional Analysis · Mathematics 2023-04-04 Marek Cúth , Michal Doucha , Ondřej Kurka

High-dimensional data arise routinely in modern statistics, econometrics, finance, genomics, and machine learning. While a large body of existing methodology is developed under Gaussian or light-tailed assumptions, many real data sets…

Methodology · Statistics 2026-04-16 Long Feng

Embeddings play a pivotal role across various disciplines, offering compact representations of complex data structures. Randomized methods like Johnson-Lindenstrauss (JL) provide state-of-the-art and essentially unimprovable theoretical…

Machine Learning · Statistics 2024-12-11 Nikos Tsikouras , Constantine Caramanis , Christos Tzamos

The holographic entropy cone (HEC) is a polyhedral cone first introduced in the study of a class of quantum entropy inequalities. It admits a graph-theoretic description in terms of minimum cuts in weighted graphs, a characterization which…

Combinatorics · Mathematics 2023-01-10 David Avis , Sergio Hernández-Cuenca

There has been growing attention on how to effectively and objectively use covariate information when the primary goal is to estimate the average treatment effect (ATE) in randomized clinical trials (RCTs). In this paper, we propose an…

Methodology · Statistics 2020-09-01 Yuanyao Tan , Xialing Wen , Wei Liang , Ying Yan

We investigate the extent to which advances in the health and life sciences (HLS) are dependent on research in the engineering and physical sciences (EPS), particularly physics, chemistry, mathematics, and engineering. The analysis combines…

Digital Libraries · Computer Science 2017-02-08 Ludo Waltman , Anthony F. J. van Raan , Sue Smart

These notes are based on a series of lectures given first at the University of Warwick in spring 2008 and then at the Courant Institute, Imperial College London, and EPFL. It is an attempt to give a reasonably self-contained presentation of…

Probability · Mathematics 2023-07-04 Martin Hairer

This article is dedicated to Elliott Lieb in celebration of his 90th birthday. I recount briefly some history of our joint work on the existence of the thermodynamic limit for Coulomb systems and discuss, even more briefly, two open…

Mathematical Physics · Physics 2022-02-04 Joel L. Lebowitz

Multiregional input-output (MRIO) tables, in conjunction with Leontief analysis, are widely-used to assess the geographical distribution of carbon emissions and the economic activities that cause them. Majorization, a tool originating in…

Physics and Society · Physics 2021-11-16 Samuel P. Loomis , Mark Cooper , James P. Crutchfield

Metric embedding is a powerful tool used extensively in mathematics and computer science. We devise a new method of using metric embeddings recursively, which turns out to be particularly effective in $\ell_p$ spaces, $p>2$, yielding…

Computational Geometry · Computer Science 2025-04-08 Robert Krauthgamer , Nir Petruschka , Shay Sapir
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