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We obtain a measure theoretical characterization of polynomials among rational functions on $\mathbb{P}^1$, which generalizes a theorem of Lopes. Our proof applies both classical and dynamically weighted potential theory.

Complex Variables · Mathematics 2012-10-19 Yûsuke Okuyama , Małgorzata Stawiska

Counting how many particles pass through a specific space within a specific time is an interesting question in applied physics and social science. Here a logistic model is developed to estimate the total number of flowing particles. This…

Physics and Society · Physics 2020-03-30 Byung Mook Weon

We introduce a novel neural network-based algorithm to compute optimal transport (OT) plans for general cost functionals. In contrast to common Euclidean costs, i.e., $\ell^1$ or $\ell^2$, such functionals provide more flexibility and allow…

Machine Learning · Computer Science 2024-05-31 Arip Asadulaev , Alexander Korotin , Vage Egiazarian , Petr Mokrov , Evgeny Burnaev

In several FICO studies logistic regression has been shown to be a very competitive technology for developing unrestricted scoring models, especially for performance metrics like ROC area. Application of logistic regression has been…

Methodology · Statistics 2020-03-03 Bruce Hoadley

In this paper we present a Maple library (MOPs) for computing Jack, Hermite, Laguerre, and Jacobi multivariate polynomials, as well as eigenvalue statistics for the Hermite, Laguerre, and Jacobi ensembles of Random Matrix theory. We also…

Mathematical Physics · Physics 2007-05-23 Ioana Dumitriu , Alan Edelman , Gene Shuman

Let $\pi_{0}$ and $\pi_{1}$ be two distributions on the Borel space $(\mathbb{R}^{d},\mathcal{B}(\mathbb{R}^{d}))$. Any measurable function $T:\mathbb{R}^{d}\rightarrow\mathbb{R}^{d}$ such that $Y=T(X)\sim\pi_{1}$ if $X\sim\pi_{0}$ is…

Computation · Statistics 2020-01-22 Jeremy Heng , Arnaud Doucet , Yvo Pokern

Some top-down problem specifications, if executed directly, may compute sub-problems repeatedly. Instead, we may want a bottom-up algorithm that stores solutions of sub-problems in a table to be reused. It can be tricky, however, to figure…

Programming Languages · Computer Science 2024-03-05 Shin-Cheng Mu

Logistic regression is a fundamental and widely used statistical method for modeling binary outcomes based on covariates. However, the presence of missing data, particularly in settings involving hybrid covariates (a mix of discrete and…

Methodology · Statistics 2025-06-05 Mohamed Cherifi , Xujia Zhu , Mohammed Nabil El Korso , Ammar Mesloub

In this note, we illustrate the computation of the approximation of the supply curves using a one-step basis. We derive the expression for the L2 approximation and propose a procedure for the selection of nodes of the approximation. We…

Pricing of Securities · Quantitative Finance 2023-11-21 Andres M. Alonso , Zehang Li

We construct inducing schemes for general multi-dimensional piecewise expanding maps where the base transformation is Gibbs-Markov and the return times have exponential tails. Such structures are a crucial tool in proving statistical…

Dynamical Systems · Mathematics 2020-02-18 Peyman Eslami

We model the logarithm of the price (log-price) of a financial asset as a random variable obtained by projecting an operator stable random vector with a scaling index matrix $\underline{\underline{E}}$ onto a non-random vector. The scaling…

Probability · Mathematics 2015-06-26 Przemysław Repetowicz , Peter Richmond

This paper considers the problem of matrix-variate logistic regression. It derives the fundamental error threshold on estimating low-rank coefficient matrices in the logistic regression problem by obtaining a lower bound on the minimax…

Machine Learning · Computer Science 2022-05-10 Batoul Taki , Mohsen Ghassemi , Anand D. Sarwate , Waheed U. Bajwa

A simple and algorithmic description of matrix shape invariant potentials is presented. The complete lists of generic matrix superpotentials of dimension $2\times2$ and of special superpotentials of dimension $3\times3$ are given…

Mathematical Physics · Physics 2012-01-25 Anatoly G. Nikitin , Yuri Karadzhov

We consider the three-loop singlet diagrams induced by axial-vector, scalar and pseudo-scalar currents. Expansions for small and large external momentum $q$ are presented. They are used in combination with conformal mapping and Pad\'e…

High Energy Physics - Phenomenology · Physics 2016-08-25 K. G. Chetyrkin , R. Harlander , M. Steinhauser

Using the free-space translation representation (modified Radon transform) of Lax and Phillips in odd dimensions, it is shown that the generalized backscattering transform (so outgoing angle $\omega =S\theta$ in terms of the incoming angle…

Analysis of PDEs · Mathematics 2008-01-03 Richard Melrose , Gunther Uhlmann

This paper studies the nature of fractional linear transformations in a general relativity context as well as in a quantum theoretical framework. Two features are found to deserve special attention: the first is the possibility of…

General Relativity and Quantum Cosmology · Physics 2021-07-23 Vito Flavio Bellino , Giampiero Esposito

Random matrix theory of the transition strengths is applied to transport in the strongly localized regime. The crossover distribution function between the different ensembles is derived and used to predict quantitatively the {\sl universal}…

Condensed Matter · Physics 2009-10-22 Y. Meir , O. Entin-Wohlman

In this paper we calculate the leading divergences of the effective potential for an arbitrary scalar theory on a curved spacetime background. Based on the recurrence relation between the leading poles following from the locality condition,…

High Energy Physics - Theory · Physics 2025-07-21 V. A. Filippov , R. M. Iakhibbaev , D. M. Tolkachev

The inverse of an $\infty \times \infty$ symmetric band matrix can be constructed in terms of a matrix continued fraction. For Hamiltonians with Coulomb plus polynomial potentials, this results in an exact and analytic Green's operator…

Nuclear Theory · Physics 2013-10-30 N. C. Brown , S. E. Grefe , Z. Papp

Probability functions appear in constraints of many optimization problems in practice and have become quite popular. Understanding their first-order properties has proven useful, not only theoretically but also in implementable algorithms,…

Optimization and Control · Mathematics 2023-04-21 Wim van Ackooij , Pedro Pérez-Aros , Claudia Soto
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