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Doubly intractable distributions arise in many settings, for example in Markov models for point processes and exponential random graph models for networks. Bayesian inference for these models is challenging because they involve intractable…

Computation · Statistics 2019-04-03 Jaewoo Park , Murali Haran

We introduce a subexponential algorithm for geometric solving of multivariate polynomial equation systems whose bit complexity depends mainly on intrinsic geometric invariants of the solution set. From this algorithm, we derive a new…

alg-geom · Mathematics 2008-02-03 M. Giusti , J. Heintz , K. Hägele , J. E. Morais , L. M. Pardo , J. L. Montaña

Approximate Bayesian computation (ABC) using a sequential Monte Carlo method provides a comprehensive platform for parameter estimation, model selection and sensitivity analysis in differential equations. However, this method, like other…

Machine Learning · Statistics 2015-07-21 Sanmitra Ghosh , Srinandan Dasmahapatra , Koushik Maharatna

Provided a special function of one variable and some of its derivatives can be accurately computed over a finite range, a method is presented to build a series of polynomial approximations of the function with a defined relative error over…

Computational Physics · Physics 2007-05-23 C. Semay

In the present paper we extend the multiplicative integral to complex-valued functions of complex variable. The main difficulty in this way, that is the multi-valued nature of the complex logarithm, is avoided by division of the interval of…

Complex Variables · Mathematics 2013-08-01 Agamirza E. Bashirov and , Mustafa Riza

We propose a computational method (with acronym ALDI) for sampling from a given target distribution based on first-order (overdamped) Langevin dynamics which satisfies the property of affine invariance. The central idea of ALDI is to run an…

Numerical Analysis · Mathematics 2020-04-10 Alfredo Garbuno-Inigo , Nikolas Nüsken , Sebastian Reich

We introduce floating bodies for convex, not necessarily bounded subsets of $\mathbb{R}^n$. This allows us to define floating functions for convex and log concave functions and log concave measures. We establish the asymptotic behavior of…

Functional Analysis · Mathematics 2018-08-07 Ben Li , Carsten Schuett , Elisabeth M. Werner

We introduce a new method for estimating the parameter of the bivariate Clayton copulas within the framework of Algorithmic Inference. The method consists of a variant of the standard boot-strapping procedure for inferring random…

Machine Learning · Statistics 2019-10-08 Bruno Apolloni

Probabilistic logic programs are logic programs in which some of the facts are annotated with probabilities. This paper investigates how classical inference and learning tasks known from the graphical model community can be tackled for…

Artificial Intelligence · Computer Science 2020-02-19 Daan Fierens , Guy Van den Broeck , Joris Renkens , Dimitar Shterionov , Bernd Gutmann , Ingo Thon , Gerda Janssens , Luc De Raedt

Affine invariant points and maps for sets were introduced by Gr\"unbaum to study the symmetry structure of convex sets. We extend these notions to a functional setting. The role of symmetry of the set is now taken by evenness of the…

Functional Analysis · Mathematics 2021-04-06 Ben Li , Carsten Schütt , Elisabeth M. Werner

In this paper a spline based integral approximation is utilized to propose a sequence of approximations to the error function that converge at a significantly faster manner than the default Taylor series. The approximations can be improved…

General Mathematics · Mathematics 2022-07-27 Roy M. Howard

The notion of Boolean logic backpropagation was introduced to build neural networks with weights and activations being Boolean numbers. Most of computations can be done with Boolean logic instead of real arithmetic, both during training and…

Machine Learning · Statistics 2024-01-30 Louis Leconte

Recently, we have established and used the generalized Littlewood theorem concerning contour integrals of the logarithm of analytical function to obtain a few new criteria equivalent to the Riemann hypothesis. Here, the same theorem is…

General Mathematics · Mathematics 2022-04-28 Sergey K. Sekatskii

Existing approaches to learning to prove theorems focus on particular logics and datasets. In this work, we propose Monte-Carlo simulations guided by reinforcement learning that can work in an arbitrarily specified logic, without any human…

Artificial Intelligence · Computer Science 2022-04-07 Stanisław J. Purgał , Cezary Kaliszyk

In distributed optimization and distributed numerical linear algebra, we often encounter an inversion bias: if we want to compute a quantity that depends on the inverse of a sum of distributed matrices, then the sum of the inverses does not…

Machine Learning · Computer Science 2019-05-29 Michał Dereziński , Michael W. Mahoney

We present a novel barycentric interpolation algorithm designed for analytic functions $f\in\mathcal{A}(E)$ defined on the complex plane. The algorithm, which encompasses both polynomial and rational interpolation, is tailored to handle…

Numerical Analysis · Mathematics 2024-07-23 Kelong Zhao , shuhuang Xiang

Extending the work of Freese and Cook, which develop the basic theory of calculus and power series over real associative algebras, we examine what can be said about the logarithmic functions over an algebra. In particular, we find that for…

Rings and Algebras · Mathematics 2017-08-04 Nathan BeDell

Assumption-based argumentation (ABA) is a central structured argumentation formalism. As shown recently, answer set programming (ASP) enables efficiently solving NP-hard reasoning tasks of ABA in practice, in particular in the commonly…

Artificial Intelligence · Computer Science 2021-08-10 Tuomo Lehtonen , Johannes P. Wallner , Matti Järvisalo

Intuitionistic belief has been axiomatized by Artemov and Protopopescu as an extension of intuitionistic propositional logic by means of the distributivity scheme K, and of co-reflection $A\rightarrow\Box A$. This way, belief is interpreted…

Logic · Mathematics 2021-06-29 Cosimo Perini Brogi

A classification, according to invariant theory, of non-constant invariant Abel ODEs known as solvable and found in the literature is presented. A set of new integrable classes depending on one or no parameters, derived from the analysis of…

Mathematical Physics · Physics 2009-10-31 E. S. Cheb-Terrab , A. D. Roche