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We describe a method for the numerical evaluation of normalized versions of the associated Legendre functions $P_\nu^{-\mu}$ and $Q_\nu^{-\mu}$ of degrees $0 \leq \nu \leq 1,000,000$ and orders $-\nu \leq \mu \leq \nu$ on the interval…

Numerical Analysis · Mathematics 2018-04-04 James Bremer

This paper is devoted to parameter estimation for partially observed polynomial state space models. This class includes discretely observed affine or more generally polynomial Markov processes. The polynomial structure allows for the…

Statistics Theory · Mathematics 2025-07-11 Jan Kallsen , Ivo Richert

We introduce and elaborate a novel formalism for the manipulation and analysis of proofs as objects in a global manner. In this first approach the formalism is restricted to first-order problems characterized by condensed detachment. It is…

Logic in Computer Science · Computer Science 2024-10-31 Christoph Wernhard , Wolfgang Bibel

Permutation-based partial-correlation tests guarantee finite-sample Type I error control under any fixed design and exchangeable noise, yet their power can collapse when the permutation-augmented design aligns too closely with the covariate…

Methodology · Statistics 2025-06-04 Tianyi Wang , Guanghui Wang , Zhaojun Wang , Changliang Zou

This paper develops an algorithmic-based approach for proving inductive properties of propositional sequent systems such as admissibility, invertibility, cut-elimination, and identity expansion. Although undecidable in general, these…

Logic in Computer Science · Computer Science 2021-01-11 Carlos Olarte , Elaine Pimentel , Camilo Rocha

In reverse mathematics, is is possible to have a curious situation where we know that an implication does not reverse, but appear to have no information on on how to weaken the assumption while preserving the conclusion. A main cause of…

Logic · Mathematics 2012-12-03 Henry Towsner

Interpretability is an elusive but highly sought-after characteristic of modern machine learning methods. Recent work has focused on interpretability via $\textit{explanations}$, which justify individual model predictions. In this work, we…

Machine Learning · Computer Science 2019-10-31 David Alvarez-Melis , Hal Daumé , Jennifer Wortman Vaughan , Hanna Wallach

A formal likelihood ratio hypothesis test for the validity of a parametric regression function is proposed, using a large-dimensional, nonparametric double cone alternative. For example, the test against a constant function uses the…

Methodology · Statistics 2014-06-30 Bodhisattva Sen , Mary Meyer

In an earlier paper, a new theory of measurefree "conditional" objects was presented. In this paper, emphasis is placed upon the motivation of the theory. The central part of this motivation is established through an example involving a…

Artificial Intelligence · Computer Science 2013-04-11 I. R. Goodman

A sequence $f\colon\{1,\dots,n\}\to\mathbb{R}$ contains a permutation $\pi$ of length $k$ if there exist $i_1<\dots<i_k$ such that, for all $x,y$, $f(i_x)<f(i_y)$ if and only if $\pi(x)<\pi(y)$; otherwise, $f$ is said to be $\pi$-free. In…

Data Structures and Algorithms · Computer Science 2017-10-31 Omri Ben-Eliezer , Clément L. Canonne

For processes involving structure functions and/or fragmentation functions, arguments that there is a part that dominates the NLO corrections are briefly reviewed. The arguments are tested against more recent NLO and in particular NNLO…

High Energy Physics - Phenomenology · Physics 2010-01-18 A. P. Contogouris , G. Grispos

We consider here together the inference questions and the change-point problem in Poisson autoregressions (see Tj{\o}stheim, 2012). The conditional mean (or intensity) of the process is involved as a non-linear function of it past values…

Statistics Theory · Mathematics 2013-05-09 Paul Doukhan , William Kengne

Conditional independence (CI) tests underlie many approaches to model testing and structure learning in causal inference. Most existing CI tests for categorical and ordinal data stratify the sample by the conditioning variables, perform…

Machine Learning · Statistics 2023-07-06 Ankur Ankan , Johannes Textor

Perturbative expansions in many physical systems yield 'only' asymptotic series which are not even Borel resummable. Interestingly, the corresponding ambiguities point to nonperturbative physics. We numerically verify this renormalon…

High Energy Physics - Lattice · Physics 2020-11-03 Falk Bruckmann , Matthias Puhr

Reasoning is a crucial part of natural language argumentation. To comprehend an argument, one must analyze its warrant, which explains why its claim follows from its premises. As arguments are highly contextualized, warrants are usually…

Computation and Language · Computer Science 2022-03-07 Ivan Habernal , Henning Wachsmuth , Iryna Gurevych , Benno Stein

We study the lambda-mu-calculus, extended with explicit substitution, and define a compositional output-based interpretation into a variant of the pi-calculus with pairing that preserves single-step explicit head reduction with respect to…

Logic in Computer Science · Computer Science 2016-02-22 Steffen van Bakel , Maria Grazia Vigliotti

In this paper we present an abstraction-refinement approach to Satisfiability Modulo the theory of transcendental functions, such as exponentiation and trigonometric functions. The transcendental functions are represented as uninterpreted…

Logic in Computer Science · Computer Science 2018-01-29 Alessandro Cimatti , Alberto Griggio , Ahmed Irfan , Marco Roveri , Roberto Sebastiani

The PCP Theorem is one of the most stunning results in computational complexity theory, a culmination of a series of results regarding proof checking it exposes some deep structure of computational problems. As a surprising side-effect, it…

Computational Complexity · Computer Science 2012-07-30 Luke Mathieson

For deploying foundation models, practitioners increasingly need prescriptive scaling laws: given a pre training compute budget, what downstream accuracy is attainable with contemporary post training practice, and how stable is that mapping…

Machine Learning · Computer Science 2026-02-18 Hanlin Zhang , Jikai Jin , Vasilis Syrgkanis , Sham Kakade

A standard informal method for analyzing the asymptotic complexity of a program is to extract a recurrence that describes its cost in terms of the size of its input, and then to compute a closed-form upper bound on that recurrence. We give…

Programming Languages · Computer Science 2022-08-09 Norman Danner , Daniel R. Licata