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Related papers: Statistical properties of lambda terms

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Two formalisms, both based on context-free grammars, have recently been proposed as a basis for a non-uniform random generation of combinatorial objects. The former, introduced by Denise et al, associates weights with letters, while the…

Computation and Language · Computer Science 2012-05-04 Yann Ponty

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 formalizes a latent variable inference problem we call {\em supervised pattern discovery}, the goal of which is to find sets of observations that belong to a single ``pattern.'' We discuss two versions of the problem and prove…

Machine Learning · Statistics 2014-02-10 Jonathan H. Huggins , Cynthia Rudin

Uniquely closable skeletons of lambda terms are Motzkin-trees that predetermine the unique closed lambda term that can be obtained by labeling their leaves with de Bruijn indices. Likewise, uniquely typable skeletons of closed lambda terms…

Programming Languages · Computer Science 2017-09-14 Olivier Bodini , Paul Tarau

The goal of this paper is to demonstrate the general modeling and practical simulation of random equations with mixture model parameter random variables. Random equations, understood as stationary (non-dynamical) equations with parameters…

Computation · Statistics 2025-07-31 Wolfgang Hoegele

We present several results on counting untyped lambda terms, i.e., on telling how many terms belong to such or such class, according to the size of the terms and/or to the number of free variables.

Logic in Computer Science · Computer Science 2012-02-17 Pierre Lescanne

In the context of software testing, generating complex data inputs is frequently performed using a grammar-based specification. For combinatorial reasons, an exhaustive generation of the data -- of a given size -- is practically impossible,…

Software Engineering · Computer Science 2013-11-27 Alois Dreyfus , Pierre-Cyrille Heam , Olga Kouchnarenko

We introduce a new nameless representation of lambda terms inspired by ordered logic. At a lambda abstraction, number and relative position of all occurrences of the bound variable are stored, and application carries the additional…

Logic in Computer Science · Computer Science 2011-11-02 Andreas Abel , Nicolai Kraus

This article is devoted to the presentation of lambda_rex, an explicit substitution calculus with de Bruijn indexes and a simple notation. By being isomorphic to lambda_ex - a recent formalism with variable names -, lambda_rex accomplishes…

Logic in Computer Science · Computer Science 2011-02-21 Ariel Mendelzon , Alejandro Ríos , Beta Ziliani

We present a method which displays all palindromes of a given length from De Bruijn words of a certain order, and also a recursive one which constructs all palindromes of length $n+1$ from the set of palindromes of length $n$. We show that…

Discrete Mathematics · Computer Science 2010-02-16 M-C. Anisiu , V. Anisiu , Z. Kasa

Characterization problems in free probability are studied here. Using subordination of free additive and free multiplicative convolutions we generalize some known characterizations in free probability to random variables with unbounded…

Operator Algebras · Mathematics 2021-04-20 Wiktor Ejsmont , Uwe Franz , Kamil Szpojankowski

We explore the multiplicative statistics for a unitary random matrix ensemble with a parameter-dependent deformation inserted in the probability measure. Such deformations had been studied for a bounded or decaying parameter. In this work,…

Mathematical Physics · Physics 2025-11-17 Carla Mariana da Silva Pinheiro

This work considers the notion of random tensors and reviews some fundamental concepts in statistics when applied to a tensor based data or signal. In several engineering fields such as Communications, Signal Processing, Machine learning,…

Statistics Theory · Mathematics 2024-04-24 Divyanshu Pandey , Alexis Decurninge , Harry Leib

We propose a probability distribution for multivariate binary random variables. The probability distribution is expressed as principal minors of the parameter matrix, which is a matrix analogous to the inverse covariance matrix in the…

Methodology · Statistics 2025-12-08 Takashi Arai

We examine the distribution and popularity of different parameters (such as the number of descents, runs, valleys, peaks, right-to-left minima, and more) on the sets of increasing and flattened permutations. For each parameter, we provide…

Combinatorics · Mathematics 2024-10-22 Jean-Luc Baril , José L. Ramírez

Diagrammatic techniques to compute perturbatively the spectral properties of Euclidean Random Matrices in the high-density regime are introduced and discussed in detail. Such techniques are developed in two alternative and very different…

Disordered Systems and Neural Networks · Physics 2011-08-31 T. S. Grigera , V. Martin-Mayor , G. Parisi , P. Urbani , P. Verrocchio

This article proposes a bivariate Simplex distribution for modeling continuous outcomes constrained to the interval $(0,1)$, which can represent proportions, rates, or indices. We derive analytical expressions to calculate the dependence…

We introduce a theory of probability in $\lambda$-rings designed to efficiently describe random variables valued in multisets of complex numbers, varieties over a field, or other similar enriched settings. A key role is played by the…

Number Theory · Mathematics 2025-06-10 Sean Howe

We extend the notion of mex, which is central in combinatorial number theory, to an arbitrary combinatorial structure, and we prove a general theorem to determine the generating function of the objects having fixed mex. We then study this…

Combinatorics · Mathematics 2026-05-29 Antonio Bernini , Stefano Bilotta , Giulio Cerbai , Luca Ferrari

We consider increasingly complex models of matrix denoising and dictionary learning in the Bayes-optimal setting, in the challenging regime where the matrices to infer have a rank growing linearly with the system size. This is in contrast…

Information Theory · Computer Science 2022-09-14 Jean Barbier , Nicolas Macris