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Argumentation is the process of constructing arguments about propositions, and the assignment of statements of confidence to those propositions based on the nature and relative strength of their supporting arguments. The process is modelled…

Artificial Intelligence · Computer Science 2013-03-08 John Fox , Paul J. Krause , Morten Elvang-Gøransson

We describe briefly in this note a procedure for consistently estimating the marginal likelihood of a statistical model through a sample from the posterior distribution of the model parameters.

Statistics Theory · Mathematics 2014-06-12 Paulo C. Marques F

A descent of a labeled digraph is a directed edge (s, t) with s > t. We count strong tournaments, strong digraphs, and acyclic digraphs by descents and edges. To count strong tournaments we use Eulerian generating functions and to count…

Combinatorics · Mathematics 2020-08-10 Kassie Archer , Ira M. Gessel , Christina Graves , Xuming Liang

Writing correct distributed programs is hard. In spite of extensive testing and debugging, software faults persist even in commercial grade software. Many distributed systems, especially those employed in safety-critical environments,…

Distributed, Parallel, and Cluster Computing · Computer Science 2007-05-23 Neeraj Mittal , Vijay K. Garg

Dilation and erosion are two elementary operations from mathematical morphology, a non-linear lattice computing methodology widely used for image processing and analysis. The dilation-erosion perceptron (DEP) is a morphological neural…

Machine Learning · Computer Science 2020-04-16 Marcos Eduardo Valle

Algorithm and code to produce sequences whose members obey Gaussian distribution function is reported. Discreet and limited number of groups are defined in the distribution function, where each group is represented only with one value…

Data Analysis, Statistics and Probability · Physics 2011-12-19 Sparisoma Viridi , Veinardi Suendo

Representation learning is an approach that allows to discover and extract the factors of variation from the data. Intuitively, a representation is said to be disentangled if it separates the different factors of variation in a way that is…

Machine Learning · Computer Science 2026-02-25 Antonio Almudévar , Alfonso Ortega

We introduce a novel partial differential equations approach for addressing the problem of partisan gerrymandering. Our method is based on volume preserving curvature flow, a partial differential equation which we adapt to smooth voting…

Physics and Society · Physics 2018-06-21 Matt Jacobs , Olivia Walch

This paper presents a novel method for analytical derivations of marginal densities using the fractional derivatives of moment-generating functions. Although the method requires likelihood functions to take specific forms, its assumptions…

Methodology · Statistics 2026-04-06 Si-Yang Li , David A. van Dyk , Maximilian Autenrieth

An index $e$ in a numbering of partial-recursive functions is called minimal if every lesser index computes a different function from $e$. Since the 1960's it has been known that, in any reasonable programming language, no effective…

Logic · Mathematics 2014-09-02 Jason Teutsch , Marius Zimand

In this paper we provide a definition of fractional gradient operators, related to directional derivatives. We develop a fractional vector calculus, providing a probabilistic interpretation and mathematical tools to treat multidimensional…

Mathematical Physics · Physics 2013-05-21 M. D'Ovidio , R. Garra

Quark distribution and spectator functions are estimated in a diquark spectator model. The representation of the functions in terms of non-local operators together with the rather simple model allow estimates for the yet experimentally…

High Energy Physics - Phenomenology · Physics 2007-05-23 R. Jakob , P. J. Mulders , J. Rodrigues

We formulate the statistics of the discrete multicomponent fragmentation event using a methodology borrowed from statistical mechanics. We generate the ensemble of all feasible distributions that can be formed when a single integer…

Statistical Mechanics · Physics 2020-07-03 Themis Matsoukas

Gradient-based techniques are becoming increasingly critical in quantitative fields, notably in statistics and computer science. The utility of these techniques, however, ultimately depends on how efficiently we can evaluate the derivatives…

Computation · Statistics 2020-02-04 Michael Betancourt , Charles C. Margossian , Vianey Leos-Barajas

Several recent empirical studies demonstrate that important machine learning tasks, e.g., training deep neural networks, exhibit low-rank structure, where the loss function varies significantly in only a few directions of the input space.…

Machine Learning · Computer Science 2022-06-17 Romain Cosson , Ali Jadbabaie , Anuran Makur , Amirhossein Reisizadeh , Devavrat Shah

The paper provides an analysis of the voting method known as delegable proxy voting, or liquid democracy. The analysis first positions liquid democracy within the theory of binary aggregation. It then focuses on two issues of the system:…

Multiagent Systems · Computer Science 2017-07-28 Zoé Christoff , Davide Grossi

Coded distributed computation has become common practice for performing gradient descent on large datasets to mitigate stragglers and other faults. This paper proposes a novel algorithm that encodes the partial derivatives themselves and…

Machine Learning · Computer Science 2022-06-22 Pedro Soto , Ilia Ilmer , Haibin Guan , Jun Li

We propose a notion of a stable partition in a coalitional game that is parametrized by the concept of a defection function. This function assigns to each partition of the grand coalition a set of different coalition arrangements for a…

Computer Science and Game Theory · Computer Science 2007-05-23 Krzysztof R. Apt , Tadeusz Radzik

Permutation resemblance measures the distance of a function from being a permutation. Here we show how to determine the permutation resemblance through linear integer programming techniques. We also present an algorithm for constructing…

Combinatorics · Mathematics 2023-02-10 Li-An Chen , Robert S. Coulter

Partition functions for non-interacting particles are known to be symmetric functions. It is shown that powerful group-theoretical techniques can be used not only to derive these relationships, but also to significantly simplify calculation…

Statistical Mechanics · Physics 2009-11-07 A. B. Balantekin