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We introduce a logic for reasoning about evidence, that essentially views evidence as a function from prior beliefs (before making an observation) to posterior beliefs (after making the observation). We provide a sound and complete…

Artificial Intelligence · Computer Science 2014-07-29 Joseph Y. Halpern , Riccardo Pucella

While belief functions may be seen formally as a generalization of probabilistic distributions, the question of the interactions between belief functions and probability is still an issue in practice. This question is difficult, since the…

Logic in Computer Science · Computer Science 2011-10-03 Frederic Dambreville

Human communication is based on a variety of inferences that we draw from sentences, often going beyond what is literally said. While there is wide agreement on the basic distinction between entailment, implicature, and presupposition, the…

Computation and Language · Computer Science 2024-05-10 Polina Tsvilodub , Paul Marty , Sonia Ramotowska , Jacopo Romoli , Michael Franke

Reynold's abstraction theorem is now a well-established result for a large class of type systems. We propose here a definition of relational parametricity and a proof of the abstraction theorem in the Calculus of Inductive Constructions…

Logic in Computer Science · Computer Science 2012-09-28 Chantal Keller , Marc Lasson

Variational inference is a powerful concept that underlies many iterative approximation algorithms; expectation propagation, mean-field methods and belief propagations were all central themes at the school that can be perceived from this…

Machine Learning · Statistics 2014-09-23 Jack Raymond , Andre Manoel , Manfred Opper

In this paper we present a formalization of Intuitionistic Propositional Logic in the Lean proof assistant. Our approach focuses on verifying two completeness proofs for the studied logical system, as well as exploring the relation between…

Logic in Computer Science · Computer Science 2024-11-01 Dafina Trufaş

We obtain similar types of conclusions as that of Br\"{u}ck [1] for two differential polynomials which in turn radically improve and generalize several existing results. Moreover, a number of examples have been exhibited to justify the…

Complex Variables · Mathematics 2022-09-15 Abhijit Banerjee , Bikash Chakraborty

With the increasing adoption of predictive models trained using machine learning across a wide range of high-stakes applications, e.g., health care, security, criminal justice, finance, and education, there is a growing need for effective…

Machine Learning · Computer Science 2020-08-04 Aria Khademi , Vasant Honavar

In the refinement calculus, monotonic predicate transformers are used to model specifications for (imperative) programs. Together with a natural notion of simulation, they form a category enjoying many algebraic properties. We build on this…

Logic in Computer Science · Computer Science 2009-05-26 Pierre Hyvernat

There is currently a renewed interest in the Bayesian predictive approach to statistics. This paper offers a review on foundational concepts and focuses on predictive modeling, which by directly reasoning on prediction, bypasses inferential…

Statistics Theory · Mathematics 2024-11-22 Sandra Fortini , Sonia Petrone

Expectation is a central notion in probability theory. The notion of expectation also makes sense for other notions of uncertainty. We introduce a propositional logic for reasoning about expectation, where the semantics depends on the…

Artificial Intelligence · Computer Science 2014-07-29 Joseph Y. Halpern , Riccardo Pucella

It is well known that Brownian motion enjoys several distributional invariances such as the scaling property and the time reversal. In this paper, we prove another invariance of Brownian motion that is compatible with the time reversal. The…

Probability · Mathematics 2023-10-20 Yuu Hariya

We study the problem of conditional predictive inference on multiple outcomes missing at random (MAR) -- or equivalently, under covariate shift. While the weighted conformal prediction offers a tool for inference under covariate shift with…

Methodology · Statistics 2025-08-01 Yonghoon Lee , Edgar Dobriban , Eric Tchetgen Tchetgen

We propose a rigorous decomposition of predictive error, highlighting that not all 'irreducible' error is genuinely immutable. Many domains stand to benefit from iterative enhancements in measurement, construct validity, and modeling. Our…

Machine Learning · Computer Science 2025-02-12 Jiani Yan , Charles Rahal

This paper investigates a representation language with flexibility inspired by probabilistic logic and compactness inspired by relational Bayesian networks. The goal is to handle propositional and first-order constructs together with…

Artificial Intelligence · Computer Science 2012-07-19 Fabio Gagliardi Cozman , Cassio Polpo de Campos , Jaime Ide , Jose Carlos Ferreira da Rocha

We investigate Bayesian predictive inference for finite population quantities when there are unequal probabilities of selection. Only limited information about the sample design is available; i.e., only the first-order selection…

Methodology · Statistics 2018-04-10 Junheng Ma , Joe Sedransk , Balgobin Nandram , Lu Chen

Notions of asimulation and k-asimulation introduced in [Olkhovikov, 2011] are extended onto the level of predicate logic. We then prove that a first-order formula is equivalent to a standard translation of an intuitionistic predicate…

Logic · Mathematics 2015-04-13 Grigory K. Olkhovikov

We derive a Prolog theorem prover for an Intuitionistic Epistemic Logic by starting from the sequent calculus {\bf G4IP} that we extend with operator definitions providing an embedding in intuitionistic propositional logic ({\bf IPC}). With…

Logic in Computer Science · Computer Science 2019-09-17 Paul Tarau

Notions of k-asimulation and asimulation are introduced as asymmetric counterparts to k-bisimulation and bisimulation, respectively. It is proved that a first-order formula is equivalent to a standard translation of an intuitionistic…

Logic · Mathematics 2015-04-13 Grigory K. Olkhovikov

The goal of this note is to provide a geometric setting in which generalized arithmetic means are best predictors in an appropriate metric. This characterization provides a geometric interpretation to the concept of certainty equivalent.…

Probability · Mathematics 2020-05-19 Henryk Gzyl
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