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Existing time series tokenization methods predominantly encode a constant number of samples into individual tokens. This inflexible approach can generate excessive tokens for even simple patterns like extended constant values, resulting in…

Machine Learning · Computer Science 2026-01-29 Leon Götz , Marcel Kollovieh , Stephan Günnemann , Leo Schwinn

This is the second in a trilogy of papers introducing and studying the notion of decomposition space as a general framework for incidence algebras and M\"obius inversion, with coefficients in $\infty$-groupoids. A decomposition space is a…

Category Theory · Mathematics 2020-02-03 Imma Gálvez-Carrillo , Joachim Kock , Andrew Tonks

We take steps towards causally interpretable meta-analysis by describing methods for transporting causal inferences from a collection of randomized trials to a new target population, one-trial-at-a-time and pooling all trials. We discuss…

Maximum composite likelihood estimation is a useful alternative to maximum likelihood estimation when data arise from data generating processes (DGPs) that do not admit tractable joint specification. We demonstrate that generic composite…

Methodology · Statistics 2021-06-29 Hien D Nguyen , Jessica Bagnall-Guerreiro , Andrew T Jones

Given a submodular capacity space, we prove the uniform convergence in capacity and also the uniform convergence in the Choquet-mean of order $p\ge1$ with a quantitative estimate, of the multivariate Bernstein polynomials associated to a…

Classical Analysis and ODEs · Mathematics 2020-10-02 Sorin G. Gal , Constantin Niculescu

Using oblique projections and angles between subspaces we write condition number estimates for abstract nonsymmetric domain decomposition methods. In particular, we consider a restricted additive method for the Poisson equation and write a…

Numerical Analysis · Mathematics 2023-04-19 Juan Galvis

We propose a novel Bayesian model framework for discrete ordinal and count data based on conditional transformations of the responses. The conditional transformation function is estimated from the data in conjunction with an a priori chosen…

Methodology · Statistics 2022-05-19 Manuel Carlan , Thomas Kneib

As inductive inference and machine learning methods in computer science see continued success, researchers are aiming to describe ever more complex probabilistic models and inference algorithms. It is natural to ask whether there is a…

Logic · Mathematics 2019-11-19 Nathanael L. Ackerman , Cameron E. Freer , Daniel M. Roy

A sumset semigroup is a non-cancellative commutative monoid obtained from the sumset of finite non-negative integer sets. In this work, an algorithm for computing the ideals associated with some sumset semigroups is provided. Using these…

Number Theory · Mathematics 2021-10-06 J. I. García-García , D. Marín-Aragón , A. Vigneron-Tenorio

We explore the finite-dimensional part of the non-commutative Choquet boundary of an operator algebra. In other words, we seek finite-dimensional boundary representations. Such representations may fail to exist even when the underlying…

Operator Algebras · Mathematics 2020-09-29 Raphaël Clouâtre , Ian Thompson

Hyperbolic-spaces are better suited to represent data with underlying hierarchical relationships, e.g., tree-like data. However, it is often necessary to incorporate, through alignment, different but related representations meaningfully.…

Machine Learning · Statistics 2020-12-03 Andrés Hoyos-Idrobo

Recent research has shown growing interest in modeling hypergraphs, which capture polyadic interactions among entities beyond traditional dyadic relations. However, most existing methodologies for hypergraphs face significant limitations,…

Methodology · Statistics 2025-11-04 Shihao Wu , Gongjun Xu , Ji Zhu

We extend the construction of so-called encapsulated global summation-by-parts operators to the general case of a mesh which is not boundary conforming. Owing to this development, energy stable discretizations of nonlinear and variable…

Numerical Analysis · Mathematics 2023-05-30 Tomas Lundquist , Andrew Winters , Jan Nordström

Extending the concept of level measure $\mu(\{f\ge a\})$ we introduce a generalized level measure based on a~family of conditional aggregations operators. We investigate in detail several basic properties, including connections with the…

General Mathematics · Mathematics 2022-04-08 Michal Boczek , Ondrej Hutník , Marek Kaluszka , Miriam Kleinová

Causal structure learning has long been the central task of inferring causal insights from data. Despite the abundance of real-world processes exhibiting higher-order mechanisms, however, an explicit treatment of interactions in causal…

Machine Learning · Computer Science 2025-11-07 James Enouen , Yujia Zheng , Ignavier Ng , Yan Liu , Kun Zhang

Convolution-type integral equations arise from various fields, \textit{e.g.}, finite impulse response filters in signal processing and deblurring problems in image processing. When solving these equations, conventional numerical methods,…

Numerical Analysis · Mathematics 2026-05-11 Raymond Chan , Lingfeng Li

In a recent paper (Appl. Math. Comput. 215, 1622--1645, 2009), the authors proposed a method of summation of some slowly convergent series. The purpose of this note is to give more theoretical analysis for this transformation, including the…

Numerical Analysis · Mathematics 2016-09-06 Rafał Nowak , Paweł Woźny

We present a novel approach for estimating conditional probability tables, based on a joint, rather than independent, estimate of the conditional distributions belonging to the same table. We derive exact analytical expressions for the…

Machine Learning · Statistics 2020-08-05 L. Azzimonti , G. Corani , M. Zaffalon

We consider continuous-time equilibrium seeking in monotone aggregative games with coupling constraints. We propose semi-decentralized integral dynamics and prove their global convergence to a variational generalized aggregative or Nash…

Optimization and Control · Mathematics 2018-05-10 Claudio De Persis , Sergio Grammatico

Circuits based on sum-product structure have become a ubiquitous representation to compactly encode knowledge, from Boolean functions to probability distributions. By imposing constraints on the structure of such circuits, certain inference…

Artificial Intelligence · Computer Science 2025-02-25 Benjie Wang , Denis Deratani Mauá , Guy Van den Broeck , YooJung Choi