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Normal-form bisimilarity is a simple, easy-to-use behavioral equivalence that relates terms in $\lambda$-calculi by decomposing their normal forms into bisimilar subterms. Moreover, it typically allows for powerful up-to techniques, such as…

Logic in Computer Science · Computer Science 2023-06-22 Dariusz Biernacki , Serguei Lenglet , Piotr Polesiuk

Randomized higher-order computation can be seen as being captured by a lambda calculus endowed with a single algebraic operation, namely a construct for binary probabilistic choice. What matters about such computations is the probability of…

Logic in Computer Science · Computer Science 2020-12-24 Ugo Dal Lago , Claudia Faggian , Simona Ronchi Della Rocca

This paper studies normalisation by evaluation for typed lambda calculus from a categorical and algebraic viewpoint. The first part of the paper analyses the lambda definability result of Jung and Tiuryn via Kripke logical relations and…

Logic in Computer Science · Computer Science 2022-08-19 Marcelo Fiore

In this paper, a Bayesian inference technique based on Taylor series approximation of the logarithm of the likelihood function is presented. The proposed approximation is devised for the case, where the prior distribution belongs to the…

Machine Learning · Computer Science 2015-10-06 Tohid Ardeshiri , Umut Orguner , Fredrik Gustafsson

The central role of the lexicon in Meaning-Text Theory (MTT) and other dependency-based linguistic theories cannot be replicated in linguistic theories based on context-free grammars (CFGs). We describe Tree Adjoining Grammar (TAG) as a…

cmp-lg · Computer Science 2008-02-03 Owen Rambow , Aravind Joshi

Function approximation is a generic process in a variety of computational problems, from data interpolation to the solution of differential equations and inverse problems. In this work, a unified approach for such techniques is…

Numerical Analysis · Mathematics 2019-10-01 Nikolaos P. Bakas

We propose a novel approach for parameterizing the luminosity distance, based on the use of rational "Pad\'e" approximations. This new technique extends standard Taylor treatments, overcoming possible convergence issues at high redshifts…

General Relativity and Quantum Cosmology · Physics 2015-06-19 Alejandro Aviles , Alessandro Bravetti , Salvatore Capozziello , Orlando Luongo

Approximate Bayesian computation (ABC) refers to a family of inference methods used in the Bayesian analysis of complex models where evaluation of the likelihood is difficult. Conventional ABC methods often suffer from the curse of…

Computation · Statistics 2016-07-08 Jingjing Li , David J. Nott , Yanan Fan , Scott A. Sisson

We present a technique to study normalizing strategies when termination is asymptotic, that is, it appears as a limit, as opposite to reaching a normal form in a finite number of steps. Asymptotic termination occurs in several settings,…

Logic in Computer Science · Computer Science 2022-05-24 Claudia Faggian , Giulio Guerrieri

There is increasing interest within the research community in the design and use of recursive probability models. Although there still remains concern about computational complexity costs and the fact that computing exact solutions can be…

Artificial Intelligence · Computer Science 2013-01-14 Daniel Pless , George Luger

In implementing evaluation strategies of the lambda-calculus, both correctness and efficiency of implementation are valid concerns. While the notion of correctness is determined by the evaluation strategy, regarding efficiency there is a…

Programming Languages · Computer Science 2018-02-21 Koko Muroya , Dan R. Ghica

Analyzing texts from social media encounters many challenges due to their unique characteristics of shortness, massiveness, and dynamic. Short texts do not provide enough context information, causing the failure of the traditional…

Machine Learning · Computer Science 2020-03-27 Anh Phan Tuan , Bach Tran , Thien Nguyen Huu , Linh Ngo Van , Khoat Than

Inner products of neural network feature maps arise in a wide variety of machine learning frameworks as a method of modeling relations between inputs. This work studies the approximation properties of inner products of neural networks. It…

Machine Learning · Computer Science 2024-06-18 Awni Altabaa , John Lafferty

This paper introduces a new functional expansion framework that extends classical ideas beyond the Taylor series. Unlike traditional Taylor expansions based on local polynomial approximations, the proposed approach arises from exact…

Numerical Analysis · Mathematics 2026-02-03 Junping Wang

In this paper, a new calculus on sequences is defined. Also, the $\lambda$-derivative and the $\lambda$-integration are investigated. The fundamental theorem of $\lambda$-calculus is included. A suitable function basis for the…

Combinatorics · Mathematics 2025-07-01 Ronald Orozco López

Applicative bisimilarity is a coinductive characterisation of observational equivalence in call-by-name lambda-calculus, introduced by Abramsky (1990). Howe (1996) gave a direct proof that it is a congruence, and generalised the result to…

Logic in Computer Science · Computer Science 2023-06-22 Tom Hirschowitz , Ambroise Lafont

The problem of reconstructing functions from their asymptotic expansions in powers of a small variable is addressed by deriving a novel type of approximants. The derivation is based on the self-similar approximation theory, which presents…

Statistical Mechanics · Physics 2009-11-07 S. Gluzman , V. I. Yukalov , D. Sornette

In this master's thesis, we introduce expansion systems as a general framework to describe a large variety of approximation algorithms, such as Taylor approximation, decimal expansion and continued fraction. We consider some basic…

Classical Analysis and ODEs · Mathematics 2012-06-05 V. A. Pessers

In a constructive setting, no concrete formulation of ordinal numbers can simultaneously have all the properties one might be interested in; for example, being able to calculate limits of sequences is constructively incompatible with…

Logic in Computer Science · Computer Science 2023-05-18 Nicolai Kraus , Fredrik Nordvall Forsberg , Chuangjie Xu

We reformulate an approach fist given by Barbour and Bertotti (BB) for implementing Mach's principle for nonrelativistic particles. This reformulation can deal with arbitrary symmetry groups and finite group elements. Applying these…

General Relativity and Quantum Cosmology · Physics 2010-04-14 Sean B. Gryb