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What is the proper explanation of intuitionistic hypothetical judgment, and thence propositional implication? The answer is unclear from the writings of Brouwer and Heyting, who in their lifetimes propounded multiple (sometimes conflicting)…

Logic in Computer Science · Computer Science 2015-11-30 Jonathan Sterling

In Mathematical Thought and Its Objects, Charles Parsons argues that our knowledge of the iterability of functions on the natural numbers and of the validity of complete induction is not intuitive knowledge; Brouwer disagrees on both…

History and Overview · Mathematics 2015-10-06 Mark van Atten

This paper asks what Brouwer might have replied to Dummett's interpretation of intuitionism. Complementing earlier literature, it treats Dummett's rejection of the ontological approach; the charge of psychologism and solipsism; indefinite…

History and Overview · Mathematics 2026-04-02 Mark van Atten

We introduce an axiomatization for the notion of computation. Based on the idea of Brouwer choice sequences, we construct a model, denoted by $E$, which satisfies our axioms and $E \models \mathrm{ P \neq NP}$. In other words, regarding…

Computational Complexity · Computer Science 2020-01-22 Rasoul Ramezanian

In a previous paper (of which this is a prosecution) we investigated the extraction of proof-theoretic properties of natural deduction derivations from their impredicative translation into System F. Our key idea was to introduce an extended…

Logic · Mathematics 2021-01-05 Paolo Pistone , Luca Tranchini , Mattia Petrolo

Based on an analysis of the inference rules used, we provide a characterization of the situations in which classical provability entails intuitionistic provability. We then examine the relationship of these derivability notions to uniform…

Logic in Computer Science · Computer Science 2016-08-31 Gopalan Nadathur

System F, the polymorphic lambda calculus, features the principle of impredicativity: polymorphic types may be (explicitly) instantiated at other types, enabling many powerful idioms such as Church encoding and data abstraction.…

Programming Languages · Computer Science 2022-03-04 Henry Mercer , Cameron Ramsay , Neel Krishnaswami

Both propositional dependence logic and inquisitive logic are expressively complete. As a consequence, every formula with intuitionistic disjunction or intuitionistic implication can be translated equivalently into a formula in the language…

Logic · Mathematics 2018-12-19 Fan Yang

In this article, we study predictable projections of stochastic integrals with respect to the conformal Brownian motion, extending the connection between powers of the conformal Brownian motion and the corresponding Hermite polynomials. As…

Probability · Mathematics 2012-03-16 Matteo Casserini , Freddy Delbaen

We define a computational type theory combining the contentful equality structure of cartesian cubical type theory with internal parametricity primitives. The combined theory supports both univalence and its relational equivalent, which we…

Logic in Computer Science · Computer Science 2023-06-22 Evan Cavallo , Robert Harper

A class of models is presented, in the form of continuation monads polymorphic for first-order individuals, that is sound and complete for minimal intuitionistic predicate logic. The proofs of soundness and completeness are constructive and…

Logic · Mathematics 2014-11-04 Danko Ilik

Statistics has moved beyond the frequentist-Bayesian controversies of the past. Where does this leave our ability to interpret results? I suggest that a philosophy compatible with statistical practice, labeled here statistical pragmatism,…

Other Statistics · Statistics 2011-06-23 Robert E. Kass

The intuitionistic implication and hence the notion of function space in constructive disciplines is both non-geometric and impredicative. In this paper we try to solve both of these problems by first introducing weak exponential objects as…

Logic · Mathematics 2017-11-07 Amirhossein Akbar Tabatabai

This chapter provides a overview of Bayesian inference, mostly emphasising that it is a universal method for summarising uncertainty and making estimates and predictions using probability statements conditional on observed data and an…

Methodology · Statistics 2010-02-11 Christian P. Robert , Jean-Michel Marin , Judith Rousseau

The usual reading of logical implication "A implies B" as "if A then B" fails in intuitionistic logic: there are formulas A and B such that "A implies B" is not provable, even though B is provable whenever A is provable. Intuitionistic…

Logic in Computer Science · Computer Science 2018-10-18 Andrea Condoluci , Matteo Manighetti

Parametricity states that polymorphic functions behave the same regardless of how they are instantiated. When developing polymorphic programs, Wadler's free theorems can serve as free specifications, which can turn otherwise partial…

Programming Languages · Computer Science 2024-07-09 Niek Mulleners , Johan Jeuring , Bastiaan Heeren

In Feferman's work, explicit mathematics and theories of generalized inductive definitions play a central role. One objective of this article is to describe the connections with Martin-Lof type theory and constructive Zermelo-Fraenkel set…

Logic · Mathematics 2018-01-08 Michael Rathjen

The choice of priors may become an insoluble problem if priors and Bayes' rule are not seen and accepted in the framework of subjectivism. Therefore, the meaning and the role of subjectivity in science is considered and defended from the…

Data Analysis, Statistics and Probability · Physics 2007-05-23 G. D'Agostini

Numerous approaches have been recently proposed for learning fair representations that mitigate unfair outcomes in prediction tasks. A key motivation for these methods is that the representations can be used by third parties with unknown…

Machine Learning · Computer Science 2024-06-25 Tianhao Wang , Zana Buçinca , Zilin Ma

Bayesian inference provides a uniquely rigorous approach to obtain principled justification for uncertainty in predictions, yet it is difficult to articulate suitably general prior belief in the machine learning context, where computational…

Machine Learning · Statistics 2021-03-04 Jed A. Duersch , Thomas A. Catanach
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