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We consider the mean value properties for finite variation measures with respect to a Markov operator in a discrete environnement. We prove equivalent conditions for the weak mean value property in the case of general Markov operators and…

Probability · Mathematics 2007-05-23 Fabio Zucca

We tackle the problem of conditioning probabilistic programs on distributions of observable variables. Probabilistic programs are usually conditioned on samples from the joint data distribution, which we refer to as deterministic…

Machine Learning · Computer Science 2021-03-09 David Tolpin , Yuan Zhou , Tom Rainforth , Hongseok Yang

In this paper, starting from a generalized coherent (i.e. avoiding uniform loss) intervalvalued probability assessment on a finite family of conditional events, we construct conditional probabilities with quasi additive classes of…

Artificial Intelligence · Computer Science 2012-10-19 Giuseppe Sanfilippo

We obtain, for the first time, a modular many-valued semantics for combined logics, which is built directly from many-valued semantics for the logics being combined, by means of suitable universal operations over partial non-deterministic…

Logic · Mathematics 2024-05-22 Carlos Caleiro , Sérgio Marcelino

Observables and instruments have played significant roles in recent studies on the foundations of quantum mechanics. Sequential products of effects and conditioned observables have also been introduced. After an introduction in Section~1,…

Quantum Physics · Physics 2020-05-19 Stan Gudder

Within classical propositional logic, assigning probabilities to formulas is shown to be equivalent to assigning probabilities to valuations. A novel notion of probabilistic entailment enjoying desirable properties of logical consequence is…

Logic · Mathematics 2016-01-13 Joao Rasga , Cristina Sernadas , Amilcar Sernadas

The paper studies coincidence points of parameterized set-valued mappings (multifunctions), which provide an extended framework to cover several important topics in variational analysis and optimization that include the existence of…

Optimization and Control · Mathematics 2022-03-23 Aram V. Arutyunov , Boris S. Mordukhovich , Sergey E. Zhukovskiy

Describing systems in terms of choices and their resulting costs and rewards offers the promise of freeing algorithm designers and programmers from specifying how those choices should be made; in implementations, the choices can be realized…

Logic in Computer Science · Computer Science 2024-02-14 Martin Abadi , Gordon Plotkin

We introduce the prediction value (PV) as a measure of players' informational importance in probabilistic TU games. The latter combine a standard TU game and a probability distribution over the set of coalitions. Player $i$'s prediction…

Computer Science and Game Theory · Computer Science 2017-07-10 Maurice Koster , Sascha Kurz , Ines Lindner , Stefan Napel

The valuation process that economic agents undergo for investments with uncertain payoff typically depends on their statistical views on possible future outcomes, their attitudes toward risk, and, of course, the payoff structure itself.…

Pricing of Securities · Quantitative Finance 2010-01-11 Constantinos Kardaras

Given a normalized state-vector $\psi $, we define the conditional expectation $\mathbb{E }_{\psi } (A | B ) $ of a Hermitian operator $A $ with respect to a strongly commuting family of self-adjoint operators $B $ as the best…

Quantum Physics · Physics 2024-11-14 Raymond Brummelhuis

Traditional parametric econometric models often rely on rigid functional forms, while nonparametric techniques, despite their flexibility, frequently lack interpretability. This paper proposes a parsimonious alternative by modeling the…

Methodology · Statistics 2025-02-20 Ricardo Masini , Marcelo Medeiros

This article proves the completeness of an axiomatization for initial value problems (IVPs) with compact initial conditions and compact time horizons for bounded open safety, open liveness and existence properties. Completeness…

Logic in Computer Science · Computer Science 2025-12-03 André Platzer , Long Qian

This paper presents some of the basic properties of conditioned observables in finite-dimensional quantum mechanics. We begin by defining the sequential product of quantum effects and use this to define the sequential product of two…

Quantum Physics · Physics 2020-05-12 Stan Gudder

Conformal predictors are set predictors that are automatically valid in the sense of having coverage probability equal to or exceeding a given confidence level. Inductive conformal predictors are a computationally efficient version of…

Machine Learning · Computer Science 2012-09-25 Vladimir Vovk

Our paper contributes to the theory of conditional risk measures and conditional certainty equivalents. We adopt a random modular approach which proved to be effective in the study of modular convex analysis and conditional risk measures.…

Mathematical Finance · Quantitative Finance 2022-11-10 Giulio Principi , Fabio Maccheroni

Quasi-probabilities appear across diverse areas of physics, but their conceptual foundations remain unclear: they are often treated merely as computational tools, and operations like conditioning and Bayes' theorem become ambiguous. We…

Quantum Physics · Physics 2026-02-16 Jacopo Surace

Quantum mechanics contains some strange unphysical concepts. Among these are complex numbers, Hilbert spaces with their unitary and self-adjoint operators, states represented by complex vectors, superpositions of states, collapse of wave…

Quantum Physics · Physics 2026-03-31 Stan Gudder

We extend the concept of conditional supremum to the measure-free setting of Riesz spaces via the conditional expectation operator. We explore its properties and show how this tool is crucial in generalizing various results across multiple…

Functional Analysis · Mathematics 2023-03-20 Youssef Azouzi , Mohamed Amine Ben Amor , Dorsaf Cherif , Marwa Masmoudi

Researchers in explainable artificial intelligence have developed numerous methods for helping users understand the predictions of complex supervised learning models. By contrast, explaining the $\textit{uncertainty}$ of model outputs has…

Machine Learning · Statistics 2023-11-01 David S. Watson , Joshua O'Hara , Niek Tax , Richard Mudd , Ido Guy
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