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We determine sufficient structure for an elementary topos to emulate E. Nelson's Internal Set Theory in its internal language, and show that any topos satisfying the internal axiom of choice occurs as a universe of standard objects and…

Category Theory · Mathematics 2023-09-07 José Siqueira

In this article, we develop and investigate a new classifier based on features extracted using spatial depth. Our construction is based on fitting a generalized additive model to the posterior probabilities of the different competing…

Methodology · Statistics 2015-04-16 Subhajit Dutta , Anil K. Ghosh

We introduce local expectation gradients which is a general purpose stochastic variational inference algorithm for constructing stochastic gradients through sampling from the variational distribution. This algorithm divides the problem of…

Machine Learning · Statistics 2015-03-06 Michalis K. Titsias

The Local-to-Global-Principle used in the proof of convexity theorems for momentum maps has been extracted as a statement of pure topology enriched with a structure of convexity. We extend this principle to not necessarily closed maps…

Symplectic Geometry · Mathematics 2012-02-14 Wolfgang Rump , Jenny Santoso

For a cuspidal automorphic representation of GL2/Q associated to a modular form, the local and global Langlands correspondences are compatible at all finite places of Q. On the p-adic Coleman-Mazur eigencurve this principle can fail (away…

Number Theory · Mathematics 2010-01-14 Alexander G. M. Paulin

Efficient extraction of useful knowledge from these data is still a challenge, mainly when the data is distributed, heterogeneous and of different quality depending on its corresponding local infrastructure. To reduce the overhead cost,…

Databases · Computer Science 2017-04-17 Nhien-An Le-Khac , M-Tahar Kechadi

This paper develops a general asymptotic theory of local polynomial (LP) regression for spatial data observed at irregularly spaced locations in a sampling region $R_n \subset \mathbb{R}^d$. We adopt a stochastic sampling design that can…

Statistics Theory · Mathematics 2023-12-27 Daisuke Kurisu , Yasumasa Matsuda

The goal of this paper is to show a (derived) $p$-adic Simpson correspondence for (locally) unipotent coefficients on smooth rigid-analytic varieties. Our results depend on a deformation to $\mathbf{B}_\mathtt{dr}^+/\xi^2$, and not on a…

Algebraic Geometry · Mathematics 2024-03-08 Thiago Solovera e Nery

We propose a new concept named adaptive submodularity ratio to study the greedy policy for sequential decision making. While the greedy policy is known to perform well for a wide variety of adaptive stochastic optimization problems in…

Machine Learning · Computer Science 2019-04-25 Kaito Fujii , Shinsaku Sakaue

In this paper we study the integral properties of Apollonian-3 circle packings, which are variants of the standard Apollonian circle packings. Specifically, we study the reduction theory, formulate a local-global conjecture, and prove a…

Number Theory · Mathematics 2015-04-21 Xin Zhang

Many spatial models exhibit locality structures that effectively reduce their intrinsic dimensionality, enabling efficient approximation and sampling of high-dimensional distributions. However, existing approximation techniques primarily…

Machine Learning · Statistics 2026-02-02 Tiangang Cui , Shuigen Liu , Xin T. Tong

We introduce the notions of over- and under-independence for weakly mixing and (free) ergodic measure preserving actions and establish new results which complement and extend the theorems obtained in [BoFW] and [A]. Here is a sample of…

Dynamical Systems · Mathematics 2018-07-12 Terry Adams , Vitaly Bergelson , Wenbo Sun

We develop a method of obtaining a hierarchy of new higher-order entropies in the context of compressible models with local and non-local diffusion and isentropic pressure. The local viscosity is allowed to degenerate as the density…

Analysis of PDEs · Mathematics 2019-08-07 Peter Constantin , Theodore D. Drivas , Roman Shvydkoy

In the paper, we introduce the notion of a local regular supermartingale relative to a convex set of equivalent measures and prove for it an optional Doob decomposition in the discrete case. This Theorem is a generalization of the famous…

Probability · Mathematics 2016-01-15 Nicholas Gonchar

We extend to Gaussian distributions a result providing smoothed analysis estimates for condition numbers given as relativized distances to illposedness. We also introduce a notion of local analysis meant to capture the behavior of these…

Numerical Analysis · Mathematics 2019-05-22 Felipe Cucker , Teresa Krick

We give a general local central limit theorem for the sum of two independent random variables, one of which satisfies a central limit theorem while the other satisfies a local central limit theorem with the same order variance. We apply…

Probability · Mathematics 2011-08-16 Mathew D. Penrose , Yuval Peres

Kempe, Kleinberg and Tardos (KKT) proposed the following conjecture about the general threshold model in social networks: local monotonicity and submodularity imply global monotonicity and submodularity. That is, if the threshold function…

Social and Information Networks · Computer Science 2022-01-26 Wei Chen , Qiang Li , Xiaohan Shan , Xiaoming Sun , Jialin Zhang

In this paper we deduce a graded version of Quillen--Suslin's Local-Global Principle for the traditional classical groups, viz. general linear, symplectic and orthogonal groups and establish its equivalence of the normality property of the…

K-Theory and Homology · Mathematics 2018-11-05 Rabeya Basu , Manish Kumar Singh

In this paper, we investigate the local-in-time well-posedness for the two-dimensional Prandtl equations in weighted Sobolev spaces under the Oleinik's monotonicity condition.Due to the loss of tangential derivative caused by vertical…

Analysis of PDEs · Mathematics 2018-11-30 Jincheng Gao , Daiwen Huang , Zheng-an Yao

We introduce a variant of the $k$-nearest neighbor classifier in which $k$ is chosen adaptively for each query, rather than supplied as a parameter. The choice of $k$ depends on properties of each neighborhood, and therefore may…

Machine Learning · Computer Science 2019-05-31 Akshay Balsubramani , Sanjoy Dasgupta , Yoav Freund , Shay Moran
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