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Fisher's fiducial argument is widely viewed as a failed version of Neyman's theory of confidence limits. But Fisher's goal -- Bayesian-like probabilistic uncertainty quantification without priors -- was more ambitious than Neyman's, and…

Statistics Theory · Mathematics 2023-12-25 Ryan Martin

We formalise the well-known rules of partial differentiation in a version of equational logic with function variables and binding constructs. We prove the resulting theory is complete with respect to polynomial interpretations. The proof…

Logic in Computer Science · Computer Science 2020-08-05 Gordon D. Plotkin

We develop a complexity theory for approximate real computations. We first produce a theory for exact computations but with condition numbers. The input size depends on a condition number, which is not assumed known by the machine. The…

Computational Complexity · Computer Science 2020-05-05 Gregorio Malajovich , Mike Shub

In this paper an approach to automated deduction under uncertainty,based on possibilistic logic, is proposed ; for that purpose we deal with clauses weighted by a degree which is a lower bound of a necessity or a possibility measure,…

Artificial Intelligence · Computer Science 2013-04-08 Didier Dubois , Jerome Lang , Henri Prade

In this paper, we introduce a general family of sequent-style calculi over the modal language and its fragments to capture the essence of all constructively acceptable systems. Calling these calculi \emph{constructive}, we show that any…

Logic · Mathematics 2022-10-18 Amirhossein Akbar Tabatabai , Raheleh Jalali

This paper provides a new and more direct proof of the assertion that a Turing computable function of the natural numbers is primitive recursive if and only if the time complexity of the corresponding Turing machine is bounded by a…

Formal Languages and Automata Theory · Computer Science 2025-10-22 Daniel G. Schwartz

Humans currently use arguments for explaining choices which are already made, or for evaluating potential choices. Each potential choice has usually pros and cons of various strengths. In spite of the usefulness of arguments in a decision…

Artificial Intelligence · Computer Science 2012-07-19 Leila Amgoud , Henri Prade

We study a class of projective transformations of spectraplexes associated with self-dual cones and, on this basis, propose a polynomial-time algorithm for convex feasibility problems with positive definite constraints. At each iteration of…

Optimization and Control · Mathematics 2025-06-19 Sergei Chubanov

We introduce a non-wellfounded proof system for intuitionistic logic extended with inductive and co-inductive definitions, based on a syntax in which fixpoint formulas are annotated with explicit variables for ordinals. We explore the…

Logic in Computer Science · Computer Science 2026-05-13 Sebastian Enqvist

We approach the sorites paradox (SP) through an observer-based and time-dependent approach to truth of vague assertions. Formally the approach gives rise to a semantics, called fluxing-object semantics (FOS), because it involves models that…

Logic · Mathematics 2026-03-13 Athanassios Tzouvaras

The ``impossibility theorem'' -- which is considered foundational in algorithmic fairness literature -- asserts that there must be trade-offs between common notions of fairness and performance when fitting statistical models, except in two…

Machine Learning · Computer Science 2023-02-14 Andrew Bell , Lucius Bynum , Nazarii Drushchak , Tetiana Herasymova , Lucas Rosenblatt , Julia Stoyanovich

We consider the hardness of approximation of optimization problems from the point of view of definability. For many NP-hard optimization problems it is known that, unless P = NP, no polynomial-time algorithm can give an approximate solution…

Logic in Computer Science · Computer Science 2019-08-30 Albert Atserias , Anuj Dawar

In a game of incomplete information, an infinite state space can create problems. When the space is uncountably large, the strategy spaces of the players may be unwieldly, resulting in a lack of measurable equilibria. When the knowledge of…

Logic · Mathematics 2011-10-17 Robert Samuel Simon

Although many investigators affirm a desire to build reasoning systems that behave consistently with the axiomatic basis defined by probability theory and utility theory, limited resources for engineering and computation can make a complete…

Artificial Intelligence · Computer Science 2013-04-11 Eric J. Horvitz

Logic rules and inference are fundamental in computer science and have been studied extensively. However, prior semantics of logic languages can have subtle implications and can disagree significantly, on even very simple programs,…

Logic in Computer Science · Computer Science 2021-10-07 Yanhong A. Liu , Scott D. Stoller

The well known Andrews-Curtis Conjecture [2] is still open. In this paper, we establish its finite version by describing precisely the connected components of the Andrews-Curtis graphs of finite groups. This finite version has independent…

Group Theory · Mathematics 2011-03-08 Alexandre V. Borovik , Alexander Lubotzky , Alexei G. Myasnikov

There is a problem with the foundations of classical mathematics, and potentially even with the foundations of computer science, that mathematicians have by-and-large ignored. This essay is a call for practicing mathematicians who have been…

Logic · Mathematics 2020-09-23 Jonathan Lenchner

This paper considers proof-theoretic semantics for necessity within Dummett's and Prawitz's framework. Inspired by a system of Pfenning's and Davies's, the language of intuitionist logic is extended by a higher order operator which captures…

Logic in Computer Science · Computer Science 2021-08-12 Nils Kürbis

An inferential model (IM) is a model describing the construction of provably reliable, data-driven uncertainty quantification and inference about relevant unknowns. IMs and Fisher's fiducial argument have similar objectives, but a…

Statistics Theory · Mathematics 2026-05-06 Ryan Martin

Geoffrion's theorem is a fundamental result from mathematical programming assessing the quality of Lagrangian relaxation, a standard technique to get bounds for integer programs. An often implicit condition is that the set of feasible…

Optimization and Control · Mathematics 2025-10-14 Santanu S. Dey , Frédéric Meunier , Diego Moran Ramirez
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